HIV/AIDS: Changes Needed to Improve the Distribution of Ryan	 
White CARE Act and Housing Funds (28-FEB-06, GAO-06-332).	 
                                                                 
Among federal efforts to address the HIV/AIDS epidemic are the	 
CARE Act of 1990 and the Housing Opportunities for Persons with  
AIDS program (HOPWA) administered by the Departments of Health	 
and Human Services (HHS) and Housing and Urban Development (HUD),
respectively. Both use formulas based upon a grantee's number of 
AIDS cases, rather than HIV and AIDS cases, to distribute funds  
to metropolitan areas, states, and territories. HIV cases must be
incorporated with AIDS cases in CARE Act formulas not later than 
fiscal year 2007. GAO was asked to examine (1) how CARE Act and  
HOPWA funds are allocated among types of services, (2) the extent
of funding distribution differences among CARE Act and HOPWA	 
grantees, and how funding formula provisions contribute to these 
differences, and (3) what distribution differences could result  
from incorporating HIV case counts in CARE Act and HOPWA funding 
formulas.							 
-------------------------Indexing Terms------------------------- 
REPORTNUM:   GAO-06-332 					        
    ACCNO:   A47957						        
  TITLE:     HIV/AIDS: Changes Needed to Improve the Distribution of  
Ryan White CARE Act and Housing Funds				 
     DATE:   02/28/2006 
  SUBJECT:   Acquired immunodeficiency syndrome 		 
	     Allocation (Government accounting) 		 
	     Data collection					 
	     Data integrity					 
	     Eligibility determinations 			 
	     Federal funds					 
	     Federal grants					 
	     Formula grants					 
	     Funds management					 
	     Health care programs				 
	     Health care services				 
	     Infectious diseases				 
	     HIV/AIDS						 
	     HUD Housing Opportunities for Persons		 
	     with AIDS Program					 
                                                                 

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GAO-06-332

     

     * HIV/AIDS
     * Changes Needed to Improve the Distribution of Ryan White CARE Act and
       Housing Funds
          * Background
               * HIV/AIDS in the United States
                    * The CARE Act
                         * CARE Act Amendments
                         * Metropolitan Statistical Areas
                         * HIV Case Counts
                    * HOPWA
               * Results in Brief
               * CARE Act and HOPWA Funds Allocated for Health Care, Housing
                 Assistance, and a Variety of Other Services
                    * More Than Half of Title I Fiscal Year 2003 Funding Was
                      Allocated for Health Care Services
                    * Over Two-thirds of Title II Fiscal Year 2003 Funding
                      Was Allocated for Medications
                    * Over Three-quarters of Title III Fiscal Year 2002
                      Funding Was Allocated for Health Care Services
                    * CARE Act Grants Funded Other Activities in Fiscal Year
                      2003
                    * Two-thirds of HOPWA Fiscal Year 2003 Funds Were Spent
                      on Housing Costs
               * Multiple Provisions Contribute to Disproportionate
                 Distribution of CARE Act and HOPWA Formula Funding
                    * CARE Act and HOPWA Grants Are Not Distributed Solely in
                      Proportion to Number of Persons Living with AIDS
                    * Provisions in HOPWA and CARE Act Funding Formulas
                      Incorporate Measures of AIDS Cases That Do Not Reflect
                      an Accurate Count of Persons Living with AIDS
                         * HOPWA Grants
                         * CARE Act Grants
                    * CARE Act Funding Provisions for Metropolitan Areas
                      Result in Disproportionate Funding
                         * Counting ELCs within EMAs Twice Results in
                           Disproportionate Funding per ELC across States and
                           Puerto Rico
                         * The Two-tiered Division of Emerging Communities
                           Results in Funding Disparities Among Metropolitan
                           Areas
                    * Hold-harmless Provisions and Grandfather Clause Protect
                      Funding of Certain CARE Act Grantees
                         * One EMA Has Been the Primary Recipient of Title I
                           Hold-harmless Funding
                         * Grandfathering Maintains Eligibility for EMAs That
                           No Longer Meet Certain Eligibility Criteria
                         * Title II Hold-harmless Funding Could Diminish ADAP
                           Severe Need Grants in the Future
                    * HOPWA Provision Restricts Bonus Grant Eligibility for
                      Some Grantees
                    * The Use of Revised OMB Metropolitan Area Definitions
                      Would Change Most EMA Boundaries, but Increase in ELCs
                      within EMAs Would Be Minimal
               * Funding Effect of Using HIV Case Counts Would Depend on
                 Multiple Factors
                    * Current HIV Case-reporting Systems Have Limitations for
                      Providing Case Counts for Funding Allocations
                    * The Use of HIV Case Counts in Funding Formulas Would
                      Have Changed the Distribution of Fiscal Year 2004 CARE
                      Act and HOPWA Funds
                         * Methodological Approaches Used
                         * Changes in CARE Act Funding Using HIV Cases and
                           Hold-harmless and Minimum-grant Provisions
                              * Title I Base Funding
                              * Title II Base Funding
                              * ADAP Base Funding
                    * Changes in CARE Act Formula Funding Would Be Larger If
                      Hold-harmless and Minimum-grant Provisions Were Not in
                      Effect
                         * Title I Base Funding
                              * Title II Base Funding
                              * ADAP Base Funding
                    * HOPWA Base Funding Would Generally Shift If HIV Cases
                      Were Used in Formula Allocations
                         * Differences in Case-reporting Systems Would Affect
                           Allocations
               * Conclusions
               * Matters for Congressional Consideration
               * Agency Comments and Our Evaluation
          * Appendix I: Objectives, Scope, and Methodology
               * Objectives
               * Scope and Methodology
                    * Allocation of CARE Act and HOPWA Funds among Service
                      Categories
                    * Funding-formula Provisions
                    * Use of HIV Cases in Formulas
          * Appendix II: CARE Act Title I Awards, Fiscal Year 2004
          * Appendix III: CARE Act Title II Awards, Fiscal Year 2004
          * Appendix IV: HOPWA Formula Grantees and Award Amounts, Fiscal
            Year 2004
          * Appendix V: HOPWA Base Funding Allocations Using Cumulative and
            Living AIDS Cases, Fiscal Year 2004
          * Appendix VI: Total CARE Act Title I and Title II Funding by State
            and Territory, Fiscal Year 2004
          * Appendix VII: HRSA's Title I EMAs, GAO-Identified Set of
            Comparable 2004 OMB-Defined Metropolitan Areas, and Changes
          * Appendix VIII: Estimated CARE Act Title I Funding Changes from
            Use of HIV Case Counts and ELCs with Hold-harmless
          * Appendix IX: Estimated CARE Act Title II Base Funding Changes
            from Use of HIV Case Counts and ELCs with Hold-harmless
          * Appendix X: Estimated CARE Act ADAP Base Funding Changes from Use
            of HIV Case Counts and ELCs with Hold-harmless
          * Appendix XI: Estimated CARE Act Title I Base Funding Changes from
            Use of HIV Case Counts and ELCs without Hold-harmless
          * Appendix XII: Estimated CARE Act Title II Base Funding Changes
            from Use of HIV Case Counts and ELCs without Hold-harmless
          * Appendix XIII: Estimated CARE Act ADAP Base Funding Changes from
            Use of HIV Case Counts and ELCs without Hold-harmless
          * Appendix XIV: Estimated HOPWA Base Funding Changes from Use of
            HIV and Living AIDS Case Counts, Fiscal Year 2004
          * Appendix XV: Comments from the Department of Health and Human
            Services
          * Appendix XVI: Comments from the Department of Housing and Urban
            Development
          * Appendix XVII: GAO Contact and Staff Acknowledgments
               * GAO Contact
               * Acknowledgments
          * Related GAO Products
               * Order by Mail or Phone

Report to Congressional Requesters

United States Government Accountability Office

GAO

February 2006

HIV/AIDS

Changes Needed to Improve the Distribution of Ryan White CARE Act and
Housing Funds

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GAO-06-332

Contents

Letter 1

Background 6
Results in Brief 14
CARE Act and HOPWA Funds Allocated for Health Care, Housing Assistance,
and a Variety of Other Services 17
Multiple Provisions Contribute to Disproportionate Distribution of CARE
Act and HOPWA Formula Funding 21
Funding Effect of Using HIV Case Counts Would Depend on Multiple Factors
45
Conclusions 63
Matters for Congressional Consideration 64
Agency Comments and Our Evaluation 65
Appendix I Objectives, Scope, and Methodology 69
Objectives 69
Scope and Methodology 69
Appendix II CARE Act Title I Awards, Fiscal Year 2004 80
Appendix III CARE Act Title II Awards, Fiscal Year 2004 82
Appendix IV HOPWA Formula Grantees and Award Amounts, Fiscal Year 2004 84
Appendix V HOPWA Base Funding Allocations Using Cumulative and Living AIDS
Cases, Fiscal Year 2004 88
Appendix VI Total CARE Act Title I and Title II Funding by State and
Territory, Fiscal Year 2004 92
Appendix VII HRSA's Title I EMAs, GAO-Identified Set of Comparable 2004
OMB-Defined Metropolitan Areas, and Changes 94
Appendix VIII Estimated CARE Act Title I Funding Changes from Use of HIV
Case Counts and ELCs with Hold-harmless 99
Appendix IX Estimated CARE Act Title II Base Funding Changes from Use of
HIV Case Counts and ELCs with Hold-harmless 101
Appendix X Estimated CARE Act ADAP Base Funding Changes from Use of HIV
Case Counts and ELCs with Hold-harmless 103
Appendix XI Estimated CARE Act Title I Base Funding Changes from Use of
HIV Case Counts and ELCs without Hold-harmless 105
Appendix XII Estimated CARE Act Title II Base Funding Changes from Use of
HIV Case Counts and ELCs without Hold-harmless 107
Appendix XIII Estimated CARE Act ADAP Base Funding Changes from Use of HIV
Case Counts and ELCs without Hold-harmless 109
Appendix XIV Estimated HOPWA Base Funding Changes from Use of HIV and
Living AIDS Case Counts, Fiscal Year 2004 111
Appendix XV Comments from the Department of Health and Human Services 115
Appendix XVI Comments from the Department of Housing and Urban Development
120
Appendix XVII GAO Contact and Staff Acknowledgments 127
Related GAO Products 128

Tables

Table 1: CARE Act Programs, 2004 9
Table 2: Description of CARE Act Title I and Title II Formula Grants 11
Table 3: Relationship between ELCs in EMAs and Total CARE Act Title I and
II Funding per ELC, Fiscal Year 2004 28
Table 4: Title II Emerging Communities in Fiscal Year 2004 30
Table 5: Title I Hold-harmless Funding, Fiscal Year 2004 33
Table 6: Grandfathered EMAs, Fiscal Year 2004 36
Table 7: States That Received Title II Hold-harmless Funding from Severe
Need Set-aside, Fiscal Year 2004 39
Table 8: Fiscal Year 2004 HOPWA Formula Funding 40
Table 9: CDC Acceptance of HIV Case Counts and Year of Establishment of
HIV-reporting Systems, December 2005 48
Table 10: Reported HIV Cases and ELCs as of June 2003 61
Table 11: U.S. Census Bureau Regions 78
Table 12: EMAs with Service Area Changes 94
Table 13: EMAs with No Service Area Changes 97

Figures

Figure 1: Federal HIV/AIDS Funding by Category, Fiscal Year 2004 8
Figure 2: Allocation of CARE Act Title I Funds, Fiscal Year 2003 18
Figure 3: Allocation of CARE Act Title II Funds, Fiscal Year 2003 19
Figure 4: Allocation of CARE Act Title III Funds, Fiscal Year 2002 20
Figure 5: Allocation of HOPWA Funds, Fiscal Year 2003 21

Abbreviations

ADAP AIDS Drug Assistance Program AIDS acquired immunodeficiency syndrome
CARE Act Ryan White Comprehensive AIDS Resources Emergency Act CDC Centers
for Disease Control and Prevention ELC estimated living AIDS case EMA
eligible metropolitan area EMSA eligible metropolitan statistical area HHS
Department of Health and Human Services HIV human immunodeficiency virus
HOPWA Housing Opportunities for Persons with AIDS program HRSA Health
Resources and Services Administration HUD Department of Housing and Urban
Development IOM Institute of Medicine MSA metropolitan statistical area
OMB Office of Management and Budget

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separately.

United States Government Accountability Office

Washington, DC 20548

February 28, 2006

The Honorable Michael B. Enzi Chairman Committee on Health, Education,
Labor, and Pensions United States Senate

The Honorable Mark E. Souder Chairman Subcommittee on Criminal Justice,
Drug Policy and Human Resources Committee on Government Reform House of
Representatives

The Honorable Tom A. Coburn United States Senate

The Honorable Judd Gregg United States Senate

It has been nearly 25 years since the first cases of acquired
immunodeficiency syndrome (AIDS) in the United States were identified.
Treatment advances in combination antiretroviral therapy during the 1990s
have significantly reduced AIDS mortality and slowed the progression from
a positive human immunodeficiency virus (HIV) diagnosis to AIDS. 1 Yet the
number of new HIV infections, which is estimated at 40,000 annually, has
not decreased. The Centers for Disease Control and Prevention (CDC)
estimate that between 1,039,000 and 1,185,000 people in the United States
were living with HIV/AIDS at the end of 2003. The number of people
infected with HIV/AIDS is likely to have risen since then, and CDC
estimates that, as of December 2004, it included 415,193 individuals with
AIDS.

Among the federal government's efforts to address the HIV/AIDS epidemic
are the Ryan White Comprehensive AIDS Resources Emergency Act of 1990
(CARE Act) 2 and the Housing Opportunities for Persons with AIDS program
(HOPWA). The CARE Act, which is administered by the Department of Health
and Human Services's (HHS) Health Resources and Services Administration
(HRSA), established a number of grant programs through which funds are
made available to states-including the District of Columbia-territories, 3
and metropolitan areas to provide health care, medications, and support
services to individuals and families affected by HIV/AIDS. The AIDS
Housing Opportunity Act, which was enacted in 1990 and is administered by
the Department of Housing and Urban Development (HUD), established HOPWA.
4 HOPWA provides housing assistance for low-income persons with HIV/AIDS
and their families. In fiscal year 2004, over $2 billion was distributed
through the CARE Act and $295 million was distributed through HOPWA.

1HIV is the virus that causes AIDS. Throughout this report, we use the
common term "HIV/AIDS" to refer to HIV disease, inclusive of cases that
have progressed to AIDS. When we use these terms alone, HIV refers to the
disease without the presence of AIDS, and AIDS refers exclusively to HIV
disease that has progressed to AIDS.

2Pub. L. No. 101-381, 104 Stat. 576 (codified as amended at 42 U.S.C. S:S:
300ff-300ff-111 (2000)). Unless otherwise indicated, references to the
CARE Act are to current law.

3In addition to the 50 states, the CARE Act authorizes grants to the
District of Columbia, the Commonwealth of Puerto Rico, Guam, the Virgin
Islands, American Samoa, the Commonwealth of the Northern Mariana Islands,
the Republic of the Marshall Islands, the Federated States of Micronesia,
and the Republic of Palau. Throughout this report, the term state refers
to the 50 states and the District of Columbia, and territory refers to
these listed territories.

4Pub. L. No. 101-625, tit. VIII, subtit. D, 104 Stat. 4079, 4375 (codified
as amended at 42 U.S.C. S:S: 12901-12912 (2000)). Unless otherwise
indicated, references to HOPWA are to the program as administered under
current law.

5Pub. L. No. 106-345, S: 206(b), 114 Stat. 1319, 1334-35.

6GAO, Ryan White CARE Act: Opportunities to Enhance Funding Equity,
GAO/T-HEHS-00-150 (Washington, D.C.: July 11, 2000), 6.

7Our analyses of CARE Act and HOPWA funding-formula provisions and the use
of HIV cases in making CARE Act and HOPWA funding allocations include the
states, Puerto Rico, and metropolitan areas eligible for funding.

8In this report, cumulative AIDS cases are the total number of AIDS cases,
both living and dead, reported in a jurisdiction in a given period.

9The 1990 CARE Act added a new title XXVI to the Public Health Service
Act. In general, because Part A of that new title, which authorizes grants
to metropolitan areas, was established by Title I of the CARE Act, it is
commonly referred to as Title I, and because part B, which authorizes
grants to states and territories, was established by Title II of the CARE
Act, it is commonly referred to as Title II. Titles III and IV of the Act
established Parts C and D, respectively, authorizing grants for early
intervention services as well as grants for services to women and
children, among other things. Under Title I, a metropolitan area with a
population of at least 500,000 and more than 2,000 reported AIDS cases in
the last 5 calendar years is eligible to receive Title I funding, and is
defined as an EMA.

10Under HOPWA, cumulative AIDS cases are the total AIDS cases reported in
a jurisdiction since the beginning of the epidemic in 1981.

11Under HOPWA there is a single formula grant for each grantee. It
consists of funding determined using a base factor and funding determined
using a bonus factor (which may be zero). In this report, we use the terms
base grants and bonus grants to differentiate between funding determined
using these factors.

12Bonus grants are awarded to EMSAs that have a higher-than-average per
capita incidence of AIDS over the previous year. Allocations are based on
the number of cases in excess of the average AIDS incidence rates of
EMSAs.

13In our November 1995 report, we showed that differences under the CARE
Act in funding per living AIDS case were not related to cost differences.
For a discussion of this issue as well as criteria for distributing funds,
see GAO, Ryan White CARE Act of 1990: Opportunities to Enhance Funding
Equity, GAO/HEHS-96-26 (Washington, D.C.: Nov. 13, 1995).

14For our CARE Act analyses, we used ELCs as our measure of living AIDS
cases. For HOPWA we used a measure of living AIDS cases calculated by
subtracting the number of reported deaths among AIDS cases in a
jurisdiction from the number of reported cases. In our analysis of HOPWA,
we used living AIDS cases instead of cumulative AIDS cases, which is the
measure currently required by law to be used to determine HOPWA base
funding. Consequently, our analyses of HOPWA funding reflect the effect of
using HIV and living AIDS cases instead of cumulative AIDS cases. We do
not compare how allocations could be affected if HIV cases and cumulative
cases were used to determine funding.

15Prevalence reflects the number of people living with the disease.

16In addition to the 50 states, these grants are authorized to the
District of Columbia, the Commonwealth of Puerto Rico, Guam, and the
Virgin Islands.

17All EMAs received a supplemental grant in fiscal year 2004.

18Pub. L. No. 104-146, 110 Stat. 136.

19Pub. L. No. 106-345, 114 Stat. 1319.

20HRSA calculates a jurisdiction's ELCs by using data from CDC on the
reported AIDS case counts for the last 10 years and weighting those
numbers to account for the likelihood of deaths. We used this measure as
our estimate of living AIDS cases in our analyses of CARE Act
funding-formula provisions and the use of HIV cases in CARE Act funding
formulas.

21See GAO, Ryan White CARE Act of 1990: Opportunities Are Available to
Improve Funding Equity, GAO/T-HEHS-95-126 (Washington, D.C.: Apr. 5,
1995).

22In 2005, OMB issued 2004 MSA definitions using fundamentally revised
standards issued in 2000 and data from the 2000 census. In an attempt to
make the classification of areas simpler and more transparent than the
previous standards, OMB's 2000 standards introduced new terminology and
employed new criteria for identifying central counties and their outlying
counties, and did not seek to conform with past standards nor to preserve
past metropolitan status.

2342 U.S.C. S:S: 300 ff-13(a)(3)(D)(i) and 300ff-28(a)(2)(D)(i) (2000).

24Institute of Medicine of the National Academies, Measuring What Matters:
Allocation, Planning, and Quality Assessment for the Ryan White CARE Act
(Washington, D.C.: The National Academies Press, 2004).

25Fiscal year 2002 allocations were the most recent funding data available
for Title III.

26The CARE Act requires that grantees' administrative costs not exceed 5
percent of the Title I funds awarded. Each EMA must establish a planning
council, which sets spending priorities according to local unmet needs.

27The CARE Act requires that grantees not use more than 10 percent of
Title II funds for administration. The combined funding for
administration, planning, and program evaluation may not exceed 15 percent
of a Title II grantee's award.

28The CARE Act requires that grantees not use more than 10 percent of
Title III funds for administration costs, including planning and
evaluation.

29Unless otherwise indicated, we use the term grantees to indicate the
jurisdictions on which our analyses are based, that is, the states, Puerto
Rico, and metropolitan areas.

30ELCs are the 10-year weighted estimate of living AIDS cases as specified
in the CARE Act. HRSA calculates a jurisdiction's ELCs by using data from
CDC on the reported AIDS case counts for the last 10 years. Data for each
of the 10 years are adjusted to take into account the number of deaths in
each year. However, rather that simply subtracting the number of deceased
cases in each jurisdiction, the number of reported cases is adjusted by
the national average death rate among AIDS cases.

31In this report, cumulative AIDS cases are the total number of AIDS
cases, both living and dead, reported in a jurisdiction in a given period.
Under HOPWA, cumulative AIDS cases encompass all reported cases since the
beginning of the epidemic in 1981. By statute, 75 percent of HOPWA formula
funding is allocated on the basis of cumulative AIDS cases.

32In the absence of a measure of living AIDS cases used for HOPWA funding,
we used a measure of living AIDS cases calculated by subtracting the
number of reported deaths among AIDS cases in a jurisdiction from the
number of reported cases. This measure of living AIDS cases is used for
illustrative purposes only.

33Until fiscal year 2006, bonus funding was based on the per capita
incidence of AIDS over a 1-year period. As a result, the amount of bonus
funding a grantee received could vary significantly from year to year.
With respect to fiscal year 2006 funding, HUD's appropriation act included
a provision to help mitigate this variability by changing to the use of
data reported over a 3-year period. Pub. L. No. 109-115, S: 303(d), 119
Stat. 2396, 2460 (2005).

34Eligibility for Minority AIDS Initiative grants and grant amounts are
determined using the last 2 years of reported AIDS cases.

35GAO/HEHS-96-26, 6.

36We used living AIDS case counts as of March 31, 2003, because this date
was the cutoff for reporting AIDS cases to be used for determining fiscal
year 2004 HOPWA formula funding.

37When determining CARE Act funding for fiscal year 2004, HRSA used a
survival weight of .28 for AIDS cases that had been reported 10 years
earlier. This figure represents the proportion of persons who had been
reported with AIDS 10 years earlier and were known to be alive.

38The estimate of reported living AIDS cases was calculated by subtracting
the number of reported deaths among AIDS cases from the number of reported
AIDS cases since the beginning of the epidemic.

39For an assessment of three methods for estimating the number of persons
living with AIDS, including the method used for the CARE Act, see Centers
for Disease Control and Prevention, "AIDS Cases and Persons Living with
AIDS," HIV/AIDS Surveillance Supplemental Report, vol. 8, no. 3 (2002).

40There are three EMAs in Puerto Rico: Caguas, Ponce, and San Juan.

41For EMAs that cross state boundaries, we estimated the amount of funding
received by each state. Using data obtained from HRSA, we calculated the
number of ELCs from each state in these EMAs. We then calculated the
percentage of ELCs in each state and allocated the EMA funding to each
state according to this percentage. For example, approximately 96 percent
of the ELCs in the Boston EMA are in Massachusetts and 4 percent are in
New Hampshire. Consequently, we allocated 96 percent of the Boston EMA's
funding to Massachusetts and 4 percent to New Hampshire.

42Approximately 80 percent of Puerto Rico's ELCs are in EMAs.

43Under Title I, a metropolitan area with a population of at least 500,000
and more than 2,000 reported AIDS cases in the last 5 calendar years is
eligible to receive funding.

44We excluded from our analyses the nine states that received minimum
Title II base grant awards.

45HRSA provides Minority AIDS Initiative grants according to the number of
nonwhite reported AIDS cases in the most recent 2-year period.

46The hold-harmless provision is triggered when, because of its current
number of ELCs, an EMA would not receive at least a specified level of
base funding. Hold-harmless funding under Title I is calculated using a
base year. The base year is the year preceding the fiscal year in which
the hold-harmless provision is triggered for a particular EMA. Because the
hold-harmless provision can first be triggered in different years in
different EMAs, the base year can differ among EMAs. Under the CARE Act
Amendments of 2000, an EMA is guaranteed not less than 98 percent of its
base grant in the first year the hold-harmless is triggered, 95 percent in
the second year, 92 percent in the third year, 89 percent in the fourth
year, and 85 percent in the fifth or subsequent years.

47The funds used to meet the Title I hold-harmless requirement are
deducted from the funds otherwise available for supplemental grants before
these grants are awarded. Supplemental grants are awarded by HRSA to EMAs
using a competitive process based on the demonstration of severe need and
other criteria.

48San Francisco was the only EMA that received hold-harmless funding from
fiscal year 1999 through fiscal year 2002. In fiscal year 2003, 19
additional EMAs qualified for hold-harmless funding. Twenty-one EMAs
received hold-harmless funding in fiscal year 2004. Eleven EMAs qualified
in both fiscal years 2003 and 2004.

49This analysis shows how the hold-harmless funding would have been
distributed if it had been allocated in the same proportions as the
supplemental grant funding. For example, Newark received about 2.5 percent
of the funds available for supplemental grants and, consequently, we
allocated 2.5 percent of the $8,033,563 hold-harmless funding to Newark.
It is not possible to determine the exact effect of the hold-harmless
provision on the amount of supplemental funding for each EMA because it is
not known how the funds would have been distributed in the absence of the
hold-harmless awards.

50The CARE Act Amendments of 1996 guaranteed amounts ranging from 95 to
100 percent of the 1995 base grant. The CARE Act Amendments of 2000
guaranteed amounts ranging from 85 to 98 percent of the grant received in
a base year. The base year varies by EMA.

51The guaranteed amount is calculated by multiplying the two percentages
(89 and 95) together. In fiscal year 2004 San Francisco was guaranteed to
receive at least 89 percent of its fiscal year 2000 Title I base grant.
Its fiscal year 2000 Title I base grant was guaranteed to be no less than
95 percent of its fiscal year 1995 Title I base grant.

52To be eligible for Title I funding, a metropolitan area must have
reported a cumulative total of more than 2,000 AIDS cases during the most
recent 5 calendar years and have a population of at least 500,000. These
criteria differ from those used to calculate base grant funding
allocations, which are determined using the number of ELCs.

53The AIDS case eligibility thresholds contained in the 1990 statute were
either that an area had a cumulative total of more than 2,000 AIDS cases
(that is, more than 2,000 cases living or deceased) or greater than 25
AIDS cases per 100,000 population reported to CDC. This standard was
changed in 1996 to the current threshold of more than 2,000 reported AIDS
cases during the most recent 5 calendar years and a population of 500,000
or more.

54Both EMA eligibility and Emerging Community funding are based on the
number of AIDS cases reported in the most recent 5 calendar years.

55To be eligible for a Severe Need grant, a jurisdiction must have met one
of four eligibility criteria as of January 1, 2000. It must have limited
(1) the eligibility of ADAP clients to those with incomes at or below 200
percent of the federal poverty level, (2) the number of ADAP clients by
using medical eligibility restrictions, (3) the number of antiretroviral
drugs covered in its drug formulary, or (4) the number of opportunistic
infection medications to fewer than 10 in its drug formulary.
(Opportunistic infections are illnesses such as parasitic, viral, and
fungal infections, and some types of cancer, some of which usually do not
cause disease in people with normal immune systems.) In addition, a
jurisdiction must also have agreed to provide a 25 percent match and not
impose eligibility requirements more restrictive than those in place on
January 1, 2000. According to HRSA, grantees have provided funds or
in-kind services to meet the matching requirement.

5642 U.S.C. S: 300ff-28(a)(2)(I)(ii)(VI) (2000). Title II also contains a
hold-harmless provision that requires HRSA to consider separately Title II
base grants and ADAP base grants. For the Title II base grants, this
hold-harmless provision is funded by proportionately reducing the size of
the Title II base grants made to other jurisdictions that did not qualify
for this hold-harmless funding or receive a minimum grant . The ADAP
portion would be funded by reducing the size of the ADAP base grants made
to those grantees that did not qualify for ADAP base grant hold-harmless
funding. 42 U.S.C. S: 300ff-28(a)(2)(H) (2000).

57States and Puerto Rico, as well as EMSAs, receive HOPWA base grants that
are determined by the grantee's proportion of the total number of
cumulative AIDS cases. CDC reported that there were 5.4 AIDS cases per
100,000 people in nonmetropolitan areas in 2000 and 6.2 cases per 100,000
people in these areas in 2004.

58Twenty-five percent of HOPWA formula funding is distributed through
bonus grants. Until fiscal year 2006, bonus funding was based on the per
capita incidence of AIDS over a one-year period. As a result, the amount
of bonus funding a grantee received could vary significantly from year to
year. With respect to fiscal year 2006 funding, HUD's appropriation act
included a provision to help mitigate this variability by changing to the
use of data reported over a 3-year period.

59These funding levels were calculated by dividing a grantee's fiscal year
2004 formula allocation by the number of living cases in the jurisdiction.
If the funding had been allocated proportionally on the basis of living
AIDS cases, each grantee would have received $716 per case.

60OMB's new MSA standards and definitions represent a major break with the
classification scheme used in the past. In some instances OMB retained a
term that was used in the past, such as MSA, but OMB has altered the
meaning. As a result, 2004 MSA boundaries of some EMAs are very different
from those in 1993.

61We use the term "metropolitan area" here in a generic sense to refer to
both the MSA (metropolitan statistical area) and the metropolitan division
(OMB's newly defined term for a subdivision of the very largest MSAs).

62If Title I EMA boundaries were reconfigured to conform with new OMB
definitions, those areas outside of EMAs that are currently served by
governments under Title II would also be changed. Though the effect on
areas outside EMAs can be inferred from the changes to EMAs, we do not
explicitly report those results here.

63While we focus on Title I of the CARE Act, the Title II Emerging
Communities program also uses metropolitan area definitions and it would
also be affected if the new OMB definitions were applied. We also exclude
HOPWA from this subsection because these new OMB definitions have already
been used to determine fiscal year 2004 HOPWA grant funding. For HOPWA,
HUD implemented a different method than we use for the analysis here. HUD
provided no grandfathering of eligibility for previously designated EMSAs
and instead, among all newly defined metropolitan areas, HUD selected
those whose data qualified them to be eligible for HOPWA funding. In
contrast, in our method we assume a policy whereby the 51 current EMAs
would retain their eligibility for CARE Act Title I grants without needing
to qualify on the basis of their number of ELCs or population size, and we
selected only those new metropolitan areas (or combinations of those
areas) that most closely correspond to the geographic area of each of the
51 existing Title I EMAs.

64App. I provides further explanation of the methodology we used for
selecting those combinations of metropolitan areas that would minimize
changes to current EMAs. As shown in the tables in app. VII, our
conversion method would equate some EMAs with more than one newly defined
metropolitan area in order to minimize any change in boundaries that would
occur. For example, we equate the New Haven EMA with two newly defined
units (the New Haven MSA and the Bridgeport MSA) because the two units
together have boundaries identical to the New Haven EMA.

65The Bergen-Passaic, Jersey City, and New York City EMAs would be
consolidated into the new New York City EMA (with no change to the
geographic area encompassed and no change to the numbers of ELCs served).
The Caguas and San Juan EMAs would be consolidated into the new San Juan
EMA (with a net increase of 6 counties and 4 percent in ELCs.) Increases
or decreases in the number of outlying counties included in metropolitan
area boundaries would mostly have small effect on the numbers of ELCs
because such outlying counties have many fewer ELCs than the more populous
central counties. In those instances where EMAs would be consolidated, the
changes to boundaries would be substantial, though there would be little
or no net change in numbers of ELCs within those boundaries.

66Institute of Medicine, Measuring What Matters, 87-134. While IOM
examined only the CARE Act, its findings regarding the use of HIV data for
determining funding allocations are also relevant for HOPWA.

67In our analyses, we considered the Title I hold-harmless provision and
the Title II hold-harmless provisions that are funded by proportional
reductions in Title II base grants and ADAP base grants. We did not
include the Title II hold-harmless provision funded by amounts otherwise
available for Severe Need grants.

68See app. I for a listing of the four U.S. Census Bureau regions and the
jurisdictions that constitute each region. Because Puerto Rico is not
included in any of these four regions, we excluded it from our regional
analyses.

69HIV case-reporting systems are generally either name- or code-based. In
name-based systems, cases are collected by name while in a code-based
system cases are collected using a coded identifier. Currently, 38 states
and Puerto Rico have name-based systems while 8 states have code-based
systems. In the remaining 5 states, names are collected and converted to
codes by public health authorities.

70 GAO/T-HEHS-00-150 .

71Name-based HIV reporting has been established in all parts of
Pennsylvania except Philadelphia since 2002. Philadelphia was given
permission by the state to establish code-based HIV reporting, and the
system began in 2004. However, in August 2005, the Philadelphia Board of
Health voted to implement a name-based HIV-reporting system. This system
went into effect in October 2005. Philadelphia is in the process of having
its HIV surveillance data certified by CDC; once certified, its data will
be accepted by CDC.

72HRSA uses AIDS case counts provided by CDC for determining CARE Act
formula funding. All states and territories report AIDS cases by name.

73CDC has established a set of performance standards for accepting case
counts from HIV-reporting systems. These standards include that case
reporting be complete (greater than or equal to 85 percent of cases are
reported) and timely (greater than or equal to 66 percent of cases
reported within 6 months of diagnosis) and that evaluation studies
demonstrate that the approach must result in accurate case counts (less
than or equal to 5 percent of reported cases are duplicates). CDC has
determined that the only systems which have been evaluated that meet these
standards use confidential, name-based reporting. Some jurisdictions use
codes instead of names to secure the privacy of the individuals being
counted. In July 2005, CDC began recommending that all states and
territories adopt confidential name-based surveillance systems to report
HIV infections.

74Two of the 13 states, Illinois and Maine, established name-based HIV
reporting in January 2006.

75CDC also has other concerns about code-based reporting. For example,
code-based reporting places a greater burden on health care providers
because submitted codes are frequently incomplete and require extensive
follow-up with providers to resolve potential duplicate reports on the
same person.

76Unlike the CARE Act, there is currently no law requiring the use of HIV
cases in determining HOPWA funding. In our analysis of HOPWA, we used
living AIDS cases instead of cumulative AIDS cases, which is the measure
currently required by law to be used to determine HOPWA base funding. As
we reported in 1995, we believe that cumulative AIDS cases is an
inappropriate measure for allocating funds ( GAO/HEHS-96-26 , 6).
Consequently, our analyses of HOPWA funding reflect the effect of using
HIV and living AIDS cases instead of cumulative AIDS cases. This measure
of living AIDS cases is used for illustrative purposes only.

77We used ELCs in our analyses of CARE Act programs, which is the measure
of AIDS cases used by HRSA in determining funding for the grants we
examined: Title I, Title II, and ADAP base grants. HUD does not have a
measure of living AIDS cases that it uses to determine HOPWA funding.
Because ELCs are specific to the CARE Act and because of shortcomings in
this measure discussed earlier, we calculated an alternative measure of
living AIDS cases in our examination of HOPWA funding. For the HOPWA
analyses, the living AIDS case counts were calculated by subtracting the
number of reported deaths among AIDS cases from the number of reported
AIDS cases.

78Because HIV-reporting systems in some jurisdictions are changing to
name-based systems, CDC now accepts HIV case counts from some
jurisdictions from which it did not accept HIV case counts earlier. For
our analyses, we classified Connecticut, Kentucky, and New Hampshire as
having HIV case counts that are not accepted by CDC. Our analyses were
conducted using fiscal year 2004 allocations, which were based on case
reports as of June 30, 2003, for the CARE Act and as of March 31, 2003,
for HOPWA. At those times, Connecticut had name-based HIV reporting for
only pediatric cases, but established name-based reporting for all cases
in 2005. Kentucky had code-based reporting at that time and established
name-based reporting in 2004. New Hampshire established mandatory
name-based reporting in 2005, but previously accepted reports using the
patient name, a code, or no identifier. A fourth state, Georgia, had not
established any HIV case reporting as of June 30, 2003, but did so in
2004. Consequently, the HIV case count for Georgia is zero in our
analyses. Pennsylvania is classified as having its HIV case counts
accepted by CDC. However, these counts do not include any cases from
Philadelphia, which established its code-based system in 2004.
Philadelphia established a name-base HIV-reporting system in October 2005
and is in the process of having its HIV surveillance data certified by
CDC; once certified, its data will be accepted by CDC. Illinois and Maine
established name-based HIV-reporting systems in January 2006 and are also
in the process of having their HIV data certified by CDC; once certified,
their data will be accepted by CDC.

79CDC receives, reviews, and processes name-based HIV case reports on
individual cases. Potential duplicate reports across jurisdictions are
reviewed through a CDC-coordinated process to remove duplicate reports
from the national database. Code-based reports cannot be included in this
de-duplication process because name-based and code-based systems do not
have comparable patient identifiers. Because the name- and code-based case
counts are not comparable, in its comments on a draft of this report HHS
stated that it would not be appropriate to use the code-based case counts
in monitoring HIV/AIDS nationally. Our purpose in using both the name- and
code-based case counts was to provide a general indication of how funding
would be affected by using HIV and AIDS cases to distribute CARE Act and
HOPWA funds in light of the statutory requirement that HIV cases be used
in CARE Act funding formulas not later than fiscal year 2007. Our use of
the code-based case counts should not be taken as endorsement for their
use in monitoring HIV/AIDS or distributing funds. An assessment of the
feasibility of using code-based case counts was beyond the scope of our
report.

80HIV case counts for three states-Georgia, Kentucky, and the District of
Columbia-were unavailable. Consequently, their HIV case counts are zero
under both approaches. HIV case counts were also unavailable for
Philadelphia, and as a consequence HIV counts were incomplete for
Pennsylvania.

81For example, for CARE Act Title I base funding, we calculated the EMA's
percentage of the total number of HIV/AIDS cases in all EMAs.

82Under the CARE Act, there is a minimum-grant provision for Title II base
grants, but not for Title I and ADAP base funding. However, there are
hold-harmless provisions for Title I, Title II, and ADAP base funding.
There is no comparable hold-harmless provision in HOPWA and minimum-grant
requirements have been effectively waived in recent years. Consequently,
the analyses in which the hold-harmless and minimum-grant provisions are
maintained are limited to the CARE Act. For purposes of this analysis, we
considered the Title I hold-harmless provision and the Title II
hold-harmless provision that is funded by proportional reductions in Title
II base grants and ADAP base grants. We did not include the Title II
hold-harmless provision funded by amounts otherwise available for Severe
Need grants. The effect on HOPWA allocations are discussed later.

83There is no minimum funding provision for Title I base grants.

84See app. I for a listing of the four U.S. Census Bureau regions and the
jurisdictions that constitute each region.

85We assume that the case threshold for determining the size of minimum
grants would remain at 90 even if HIV cases were included in the case
counts. Currently, states with fewer than 90 ELCs are guaranteed a minimum
Title II base grant of $200,000 while states with 90 or more cases are
guaranteed at least $500,000. Our analyses assume that the threshold would
be a total of 90 HIV cases and ELCs.

86There is no minimum funding provision for ADAP base grants.

87The ADAP base grant funding reported to us included any hold-harmless
funding taken from funds otherwise set aside for the ADAP Severe Need
grants. This hold-harmless funding results from a different Title II
hold-harmless provision than that which requires HRSA to consider
separately Title II base grants and ADAP base grants. In our analyses, we
excluded hold-harmless funding taken from the ADAP Severe Need grants when
we estimated the dollar and percent changes in the ADAP base grants.

88For a description of features in funding formulas, see National Research
Council, Statistical Issues in Allocating Funds by Formula: Panel on
Formula Allocations (Washington, D.C.: The National Academies Press,
2003).

89In these analyses we considered the Title I hold-harmless provision and
the Title II hold-harmless provisions that are funded by proportional
reductions in Title II base grants and ADAP base grants. We did not
include the Title II hold-harmless provision funded by amounts otherwise
available for Severe Need grants.

90There is no minimum funding provision for Title I base funding.

91The amount of base grant funding would have been about $8 million less
without the hold-harmless provision. This money would have been
distributed to EMAs in supplemental grants.

92EMAs in the West would gain funding under both approaches if the
hold-harmless was maintained but would receive less funding under both
approaches if it was not maintained.

93Grantees in the West would gain funding under both approaches if the
hold-harmless and minimum-grant provisions were maintained but would
receive less funding under both approaches if they were not maintained.

94There is no minimum funding provision for ADAP base funding.

95For the HOPWA analyses, the living AIDS case counts were calculated by
subtracting the number of reported deaths among AIDS cases from the number
of reported AIDS cases.

96This analysis indicates how HOPWA base funding would have changed if
living AIDS cases and HIV cases had been used to distribute funding rather
than cumulative case counts. The effect of using living AIDS cases but not
HIV cases on HOPWA base funding is shown in app. V.

97These six grantees are the state of Alabama; Birmingham, Alabama;
Charlotte, North Carolina; Memphis, Tennessee; the state of North
Carolina; and Wake County, North Carolina.

98In those cases in which an EMSA included both southern and nonsouthern
jurisdictions, we classified the EMSA as not being in the South.

99In this instance, AIDS cases refers to ELCs for the CARE Act and
cumulative AIDS cases for HOPWA.

100Other factors may also affect the ratio of HIV to AIDS cases in a
reporting system. For example, some jurisdictions with newer HIV-reporting
systems were among the first to be affected by the HIV epidemic. This
factor could mean that in those jurisdictions there are relatively more
AIDS cases and the ratio of HIV to AIDS cases would be lower than in
jurisdictions more recently experiencing an HIV epidemic.

101Institute of Medicine, Measuring What Matters, 92.

1Grantees are those entities that receive CARE and HOPWA funding. Grantees
vary by program and can include states, territories, metropolitan areas,
and primary-care providers.

2HRSA calculates a jurisdiction's ELCs by using data from CDC on the
reported AIDS case counts for the last 10 years and weighting those
numbers to account for the likelihood of death.

3Title II also contains a hold-harmless provision that requires HRSA to
consider separately Title II base grants and ADAP base grants. For the
Title II base grants, this hold-harmless provision is funded by
proportionately reducing the size of the Title II base grants made to
other jurisdictions that did not qualify for this hold-harmless funding or
receive a minimum grant. The ADAP portion would be funded by reducing the
size of the ADAP base grants made to those grantees that did not qualify
for ADAP base grant hold-harmless funding.

4Unlike the CARE Act in which ELCs in EMAs are counted once for
determining Title I funding and a second time for determining Title II
funding, under HOPWA AIDS cases in EMSAs are counted only for determining
funding for EMSAs. These cases are not counted a second time for
determining HOPWA base funding allocations for states and territories.
Funding for states and territories is based on the number of cumulative
AIDS cases outside of EMSAs. For example, HOPWA base funding for Colorado
is based on the number of cumulative AIDS cases in the state minus the
number of cumulative cases in the Denver EMSA.

5The AIDS case count used in the analyses varied by program (e.g., ELCs
and cumulative AIDS cases).

6In our November 1995 report, we showed under the CARE Act that
differences in funding per living AIDS case were not related to cost
differences. For a discussion of this issue as well as criteria for
distributing funding per case, see GAO, Ryan White CARE Act of 1990:
Opportunities to Enhance Funding Equity, GAO/HEHS-96-26 (Washington, D.C.:
Nov. 13, 1995).

7GAO, Metropolitan Statistical Areas: New Standards and Their Impact on
Selected Federal Programs, GAO-04-758 (Washington, D.C.: June 14, 2004).

8There is no straightforward way to equate EMAs based on OMB's 1993
metropolitan areas with OMB's 2004 metropolitan areas. In developing its
2000 metropolitan area standards and its 2004 metropolitan area boundary
definitions, OMB did not seek to make them conform to past standards and
definitions. Moreover, even where OMB employed the same terminology (e.g.,
the term "metropolitan statistical area" was retained), the terms were
given new meanings.

9These include combinations of adjoining MSAs or adjoining MSAs and
metropolitan divisions. We exclude the use of the smaller micropolitan
statistical areas (a new OMB designation for less-populated areas) and
also exclude combined statistical areas (a new OMB designation for
groupings of adjacent metropolitan and micropolitan areas).

10Unlike the CARE Act, there are no requirements regarding the use of HIV
cases in determining HOPWA funding.

11In our analysis of HOPWA, we used living AIDS cases instead of
cumulative AIDS cases, which is the measure currently required by law to
be used to determine HOPWA base grant funding. Therefore, our analyses
reflect the effect of using HIV cases and living AIDS cases instead of
cumulative AIDS case counts on fiscal year 2004 HOPWA base grant funding.

12These 35 include 34 states and Puerto Rico.

13Some HIV case-reporting systems are name-based while others are
code-based. Currently, CDC will only accept name-based case counts as no
code-based system has yet met CDC's quality criteria. CDC has established
a set of performance standards for accepting case counts from
HIV-reporting systems. These standards include that case reporting be
complete (greater than or equal to 85 percent of cases are reported) and
timely (greater than or equal to 66 percent of cases reported within 6
months of diagnosis) and that evaluation studies demonstrate that the
approach must result in accurate case counts (less than or equal to 5
percent of reported cases are duplicates). CDC has determined that the
only systems that have been evaluated that meet these standards use
confidential, name-based reporting. Some jurisdictions use codes instead
of names to secure the privacy of the individuals being counted. In July
2005, CDC began recommending that all states and territories adopt
confidential, name-based surveillance systems to report HIV infections.

14Because HIV-reporting systems in some jurisdictions are changing to
name-based systems, CDC now accepts HIV case counts from some
jurisdictions from which it did not accept HIV case counts earlier. For
our analyses, we classified Connecticut, Kentucky, and New Hampshire as
having HIV case counts that are not accepted by CDC. Our analyses were
conducted using fiscal year 2004 allocations, which were based on case
reports as of June 30, 2003, for the CARE Act and as of March 31, 2003,
for HOPWA. At those times, Connecticut had name-based HIV reporting for
only pediatric cases, but established name-based reporting for all cases
in 2005. Kentucky had code-based reporting at that time and established
name-based reporting in 2004. New Hampshire established mandatory
name-based reporting in 2005, but previously accepted reports using the
patient name, a code, or no identifier. A fourth state, Georgia, had not
established any HIV case reporting as of June 30, 2003, but did so in
2004. Consequently, the HIV case count for Georgia is zero in our
analyses. Pennsylvania is classified as having its HIV case counts
accepted by CDC. However, these counts do not include any cases from
Philadelphia, which established its code-based system in 2004.
Philadelphia establsihed a name-based system in October 2005. Philadelphia
is in the process of having its HIV surveillance data certified by CDC;
once certified, its data will be accepted by CDC. Illinois and Maine
established name-based HIV-reporting systems in January 2006 and are also
in the process of having their HIV data certified by CDC; once certified,
their data will be accepted by CDC.

15HIV case counts for three of these jurisdictions, Georgia, Kentucky, and
the District of Columbia, were unavailable. Consequently, their HIV case
counts are zero under both approaches. HIV case counts were also
unavailable for Philadelphia, and as a consequence HIV counts were
incomplete for Pennsylvania.

16CDC receives, reviews, and processes name-based HIV case reports on
individual cases. Potential duplicate reports across jurisdictions are
reviewed through a CDC-coordinated process to remove duplicate reports
from the national database. Code-based reports cannot be included in this
de-duplication process because name-based and code-based systems do not
have comparable patient identifiers. Because the name- and code-based case
counts are not comparable, in its comments on a draft of this report HHS
stated that it would not be appropriate to use the code-based case counts
in monitoring HIV/AIDS nationally. Our purpose in using both the name- and
code-based case counts was to provide a general indication of how funding
would be affected by using HIV and AIDS cases to distribute CARE Act and
HOPWA funds. Our use of the code-based case counts should not be taken as
endorsement for their use in monitoring HIV/AIDS or distributing funds. An
assessment of the feasibility of using code-based case counts was beyond
the scope of our report.

17For example, for CARE Act Title I base funding, we calculated the EMA's
percentage of the total number of HIV cases and ELCs across all EMAs.

18Under the CARE Act, there is a minimum-grant provision for Title II base
grants, but not for Title I and ADAP base grants. However, there are
hold-harmless provisions for Title I, Title II, and ADAP base grants.
There are no comparable hold-harmless provisions in HOPWA and
minimum-grant requirements have been effectively waived in recent years.
Consequently, the analyses in which the hold-harmless and minimum-grant
provisions are maintained are limited to the CARE Act.

19Puerto Rico is not included in any of these regions and is, therefore,
excluded from these analyses.

20Michael Saag (paper presented at the XIV International AIDS Conference:
Plenary Session, HIV/AIDS Treatment and Care in the New Century,
Barcelona, July 2002); "UAB Announces Results of First HIV Patient Care
Cost Analysis," UAB Media Relations (Birmingham, Ala.: University of
Alabama at Birmingham, July 2002),
http://main.uab.edu/show.asp?durki=51750 (downloaded March 30, 2005).

Under the CARE Act and HOPWA, funding is distributed through a combination
of competitive grants and, in accordance with CDC data on the number of
individuals diagnosed with AIDS, formula grants. Approximately 68 percent
of CARE Act funding and 90 percent of HOPWA funding were distributed
through formula grants in fiscal year 2004. The use of AIDS cases in the
distribution of formula grants was prescribed because most jurisdictions
tracked and reported AIDS cases instead of HIV cases when the grant
programs were established. Because of concerns that a jurisdiction's
disease burden is not adequately reflected by only counting cases that
have progressed to AIDS, the Ryan White CARE Act Amendments of 2000
required the use of HIV/AIDS case counts in the distribution of formula
grants not later than fiscal year 2007. 5 We have reported that because
CARE Act grants serve persons who have been diagnosed with HIV that has
not progressed to AIDS as well as those for whom it has, it would be
reasonable to distribute funds on the basis of the total number of persons
living with HIV/AIDS. 6 Incorporating HIV data along with AIDS data would
result in targeting funds more accurately according to need. However,
because there is a lack of HIV data that are sufficiently adequate and
reliable to serve as a basis for CARE Act formula grant allocations, as of
December 2005, HIV cases have not been used in the distribution of formula
grants under the CARE Act.

Various provisions governing CARE Act and HOPWA grants affect the
distribution of funds. As Congress prepares to reauthorize CARE Act
programs, you asked us to examine how funds are distributed under the CARE
Act and HOPWA. We are reporting on (1) how CARE Act and HOPWA funds are
allocated by grantees among the types of services each program supports;
(2) the extent of funding differences among CARE Act and HOPWA grantees,
and how specific CARE Act and HOPWA funding-formula provisions contribute
to these differences; and (3) what distribution differences could result
from using HIV cases in CARE Act and HOPWA funding formulas.

To report on these issues, we reviewed the CARE Act of 1990, as well as
the 1996 and 2000 CARE Act amendments, the AIDS Housing Opportunity Act of
1990, HRSA and HUD documents on CARE Act and HOPWA funding, HUD memoranda,
Institute of Medicine (IOM) reports on the CARE Act, and other related
reports. We analyzed data, spanning from 2002 through 2004, obtained from
HRSA, HUD, and CDC. 7 We also collected data on HIV case counts from state
and local HIV/AIDS officials. We interviewed CDC, HRSA, HUD, and state
officials, as well as officials from the National Alliance of State and
Territorial AIDS Directors.

To determine how grantees allocate CARE Act and HOPWA funds by type of
service, we obtained information from HRSA and HUD on grantees' use of
funds. We analyzed these data and, where available, calculated the
percentage of total spending represented by each category of service. To
assess the reliability of HRSA and HUD data on allocations of CARE Act and
HOPWA grant funds, we interviewed agency officials about the data and
reviewed relevant documentation. We determined that the data were
sufficiently reliable for the purposes of our report.

In order to examine the effect of specific funding-formula provisions on
the distribution of fiscal year 2004 funds by HRSA and HUD under the CARE
Act and HOPWA to grantees, we first assessed the use of 2- and 5-year
cumulative AIDS case counts 8 and the use of estimated living AIDS cases
(ELC) in CARE Act programs by comparing these measures with living AIDS
case counts received from CDC. HRSA calculates a jurisdiction's ELCs by
using data from CDC on the reported AIDS case counts for the last 10 years
and weighting those numbers to account for the likelihood of deaths. We
then examined the effect of the following CARE Act formula provisions: the
counting of ELCs in eligible metropolitan areas (EMA) for both Title I and
Title II funding, 9 the dividing of Emerging Communities into two tiers
for determining funding, the Title I hold-harmless provision, the Title I
grandfather clause, and the Title II hold-harmless provision that is
funded from amounts that would otherwise be available for states with
severe need in their drug programs. To examine the effect of each
provision on the distribution of CARE Act and HOPWA funds, we measured
differences either on a per case basis, by the amount of funding received,
or both. To determine the effects of adopting the Office of Management and
Budget's (OMB) 2004 definitions of metropolitan statistical areas (MSA) on
EMAs, we compared the boundaries of existing EMAs with those that would be
created, and we determined the change in the number of ELCs that would be
counted under Title I. In addition, we examined the effect of using living
AIDS cases instead of cumulative AIDS cases 10 in making HOPWA base grant
distributions by comparing the actual funding distributions with simulated
distributions using living AIDS cases. 11 We also assessed the effect of
HOPWA bonus grants on funding for eligible metropolitan statistical areas
(EMSA) by examining the size of these grants and which EMSAs received
them. 12

In our analyses we used funding per AIDS case to illustrate the effect of
certain funding-formula provisions on the distribution of CARE Act and
HOPWA funds. There are other considerations that could be included in
funding formulas that could justify deviations from equal funding per
case. For example, differing health care and housing costs across regions
and differences in grantees' capacities to fund services from local
resources could be used as bases for distributing program funds and could
justify such deviations. 13 Currently, these considerations are not taken
into account when distributing formula grants under either the CARE Act or
HOPWA, and are not considered here. To assess the reliability of the HRSA
and HUD data on the distribution of funds under the CARE Act and HOPWA, we
asked agency officials about how the data were developed and reported. We
also reviewed relevant documentation. We determined the data were
sufficiently reliable for the purposes of our report.

To show how CARE Act and HOPWA funding could be affected by including HIV
cases in funding formulas, we examined how CARE Act and HOPWA fiscal year
2004 formula grants would have been affected by using HIV cases in
addition to living AIDS cases to determine formula funding. 14 We
undertook our analyses in light of the statutory requirement that HIV
cases be used in CARE Act funding formulas not later than fiscal year
2007. Our analyses, however, rely on data whose reliability has been
questioned. The Secretary of Health and Human Services has determined that
because of the problems associated with these data, they should not
currently be used in determining CARE Act funding. We used these data in
our analyses to give a general indication of the effect of using HIV cases
in future formula allocations as required by the CARE Act. The extent to
which the use of HIV cases could affect formula allocations cannot be
determined by these analyses because jurisdictions use different methods
to identify HIV cases, and it is unclear to what degree the resulting case
counts are comparable. However, we think our approaches in these analyses
are informative given the required incorporation of HIV cases into CARE
Act funding formulas. To assess the reliability of the case-count data, we
asked HRSA, HUD, CDC, state, and local officials a series of questions
about how the data were collected and the methods used to ensure their
accuracy. On the basis of the information provided regarding the
verification of these data, we determined these data to be sufficiently
reliable for the purposes of our analyses. Appendix I provides a more
detailed explanation of the scope and methodology for this report. We
performed our work from July 2004 through February 2006, in accordance
with generally accepted government auditing standards.

Background

In 1990, Congress passed the CARE Act and HOPWA legislation to address the
needs of jurisdictions, health care providers, and people with HIV/AIDS
and their family members. Within the CARE Act and HOPWA legislation, there
are provisions for determining the distribution of program funding.
Furthermore, amendments in 1996 and 2000 changed some CARE Act provisions,
and public debate continues on how best to measure the effect of HIV/AIDS
within the United States, and how to distribute funding accordingly.

HIV/AIDS in the United States

Over the course of the last quarter century, the HIV/AIDS epidemic has
spread to every region of the country. CDC has estimated that in the 50
states approximately 40,000 persons become infected with HIV annually.
While AIDS cases remained concentrated in metropolitan areas through 2004,
AIDS prevalence rates in nonmetropolitan areas rose. 15

The United States population living with HIV/AIDS is diverse. Racial and
ethnic minorities have been disproportionately affected by HIV/AIDS since
the beginning of the epidemic, but in 2004 African Americans accounted for
more new AIDS cases, more of those estimated to be living with AIDS, and
more of those who died with AIDS than any other racial or ethnic group.
Latinos also account for a greater proportion of AIDS cases and deaths
than their representation in the overall population.

Despite the number of deaths from AIDS and the steady increase of AIDS
prevalence, there have been successes in the fight against HIV/AIDS.
Developments in treatment have enhanced care options and can extend the
lives of those living with HIV/AIDS. The introduction of highly active
antiretroviral therapy in 1996 was followed by a decline in the number of
deaths and new AIDS cases in the United States for the first time since
the beginning of the epidemic.

The federal government's efforts to address the domestic HIV/AIDS epidemic
include providing federal funding for the following categories of
activities-treatment and income support for individuals with HIV/AIDS,
prevention efforts, and research. In fiscal year 2004, federal funding for
domestic HIV/AIDS programs was nearly $16.3 billion. Of this total, about
$2.1 billion was distributed through CARE Act programs, and $295 million
was distributed through the HOPWA program. Medicaid was the largest source
of federal assistance for HIV/AIDS health care, with $5.4 billion in
federal funding. Other large sources of federal funding for HIV/AIDS are
Medicare-$2.6 billion-and the National Institutes of Health-about $2.5
billion. Funding from other federal sources ranged from $1 million from
the Department of Labor to more than $1 billion from the Social Security
Disability Insurance Program. Figure 1 provides a breakdown of federal
HIV/AIDS funding by category.

Figure 1: Federal HIV/AIDS Funding by Category, Fiscal Year 2004

The CARE Act

The majority of CARE Act funds are distributed through four different
programs, each contained in a separate title, to the states, EMAs, and
other entities. Titles I and II of the act provide for formula grants
(base grants) to EMAs and states according to each jurisdiction's number
of ELCs relative to all EMAs and states. These titles also provide for
other grants to subsets of eligible jurisdictions either by formula or by
a competitive process. For example, in addition to AIDS Drug Assistance
Program (ADAP) base grants, Title II also authorizes grants for states and
certain territories with demonstrated need for additional funding to
support their ADAPs. 16 These grants, known as Severe Need Grants, are
funded through a set-aside of funds otherwise available for ADAP grants.
Title II also authorizes funding for "Emerging Communities," which are
communities affected by AIDS that have not had a sufficient number of AIDS
cases reported in the last 5 calendar years to be eligible for Title I
grants as EMAs. In order to address the effect of the disease on racial
and ethnic minorities, HRSA has used funds otherwise available under Title
I and Title II for Minority AIDS Initiative grants to EMAs, states, and
territories. EMAs may also receive Title I supplemental grants, which are
awarded using a competitive application process based on the demonstration
of severe need and other criteria. 17 Table 1 describes the purposes and
the grantees of each title.

Table 1: CARE Act Programs, 2004

CARE Act program    Grantees                 Purpose                       
Title I. Grants to  51 EMAsa                 Support primary health care,  
Eligible                                     medications, and a range of   
Metropolitan Areas                           services, such as case        
(EMAs)                                       management, substance abuse   
                                                treatment, housing, mental    
                                                health treatment, and         
                                                nutritional counseling.       
Title II. Grants to States and territories   Support primary and           
States and                                   home-based health care,       
Territories                                  insurance coverage,           
                                                medications, support          
                                                services, and early           
                                                intervention services, such   
                                                as HIV counseling, testing,   
                                                and referral. Funding for     
                                                AIDS Drug Assistance Programs 
                                                provides medications,         
                                                treatment adherence and       
                                                support, and health insurance 
                                                with prescription drug        
                                                benefits.                     
Title III. Early    Primary care providers,  Support comprehensive         
Intervention        including health         services including HIV        
Services, Capacity  centers, city and county counseling, testing,          
Development, and    health departments, and  outpatient medical care, and  
Planning Grants     outpatient medical       case management; funds also   
                       centers                  go toward developing HIV      
                                                service delivery systems and  
                                                building capacity to provide  
                                                services.                     
Title IV. Services  Health care facilities,  Support family-centered and   
for Women, Infants, public health agencies,  coordinated health care and   
Children, Youth,    and community-based      support services that benefit 
and Their Affected  organizations that serve children, youth, and women    
Family Members      Title IV target          living with HIV, and their    
                       populations              families. Also support        
                                                initiatives to help identify  
                                                HIV-positive pregnant women   
                                                and ensure access to prenatal 
                                                care that could prevent       
                                                perinatal transmission.       
Special Projects of University and community Support the development of    
National            clinics, evaluation      innovative models of HIV/AIDS 
Significance        centers,b local and      care that can be replicated,  
                       state health             such as interventions for     
                       departments,             HIV-positive substance        
                       community-based          abusers.                      
                       organizations, and       
                       nonprofit agencies       
AIDS Education and  4 national centers and   Conduct education and         
Training Center     11 regional centers with training programs for health  
Program             130 associated sites     care providers treating       
                                                people with HIV/AIDS.         
Dental Programs     Dental education         Improve access to oral health 
                       institutions, hospitals, care and enhance dental       
                       and other institutions   training on caring for people 
                       with dental education    with HIV/AIDS through the     
                       programs                 Dental Reimbursement Program  
                                                and Community-Based Dental    
                                                Partnership grants.           

Source: HRSA.

aUnder Title I, a metropolitan area with a population of at least 500,000
and more than 2,000 reported AIDS cases in the last 5 calendar years is
eligible to receive a formula base grant. As a result of the CARE Act
Amendments of 1996, EMAs that were eligible for Title I grants in that
year are grandfathered: they will be eligible for grants under Title I
even if their number of AIDS cases drops below the threshold for
eligibility. App. II contains a list of the EMAs.

bEvaluation centers support Special Projects grantees and coordinate the
evaluation of initiatives under the Special Projects of National
Significance program.

CARE Act Amendments

The Ryan White CARE Act Amendments of 1996 18 and the Ryan White CARE Act
Amendments of 2000 19 modified the original funding formulas. For example,
prior to the 1996 amendments, the CARE Act required that for purposes of
determining grant amounts a metropolitan area's caseload be measured by a
cumulative count of AIDS cases recorded in the jurisdiction since
reporting began in 1981. The 1996 amendments required the use of ELCs
instead of cumulative AIDS cases. 20 Because this switch would have
resulted in large shifts of funding away from jurisdictions with a longer
history of the disease than other jurisdictions, due in part to a higher
proportion of deceased cases, the 1996 CARE Act amendments added a
hold-harmless provision under Title I, as well as under Title II, that
limit the extent a grantee's funding can decline from one year to the
next.

Metropolitan areas heavily affected by HIV/AIDS have always been
recognized within the structure of the CARE Act. We previously found that,
with combined funding under Title I and Title II, states with EMAs receive
more funding per AIDS case than states without EMAs. 21 To adjust for this
situation, the 1996 amendments instituted a two-part formula for Title II
base grants that takes into account the number of ELCs that reside within
a state but outside of any EMA. Under this distribution formula, 80
percent of the Title II base grant is based upon a state's proportion of
all ELCs, and 20 percent of the base grant is based on a states'
proportion of ELCs outside of EMAs relative to all such ELCs. A second
provision included in 1996 protected the eligibility of EMAs. The 1996
amendments provided that a jurisdiction designated as an EMA for that
fiscal year would be "grandfathered" so it would continue to receive Title
I funding even if its reported number of AIDS cases dropped below the
threshold for eligibility. Table 2 describes CARE Act formula grants for
Titles I and II.

Table 2: Description of CARE Act Title I and Title II Formula Grants

Formula      Eligible      Distribution        Minimum      Hold-harmless  
grant        grantees                          grant        provisiona     
Title I Base Metropolitan  Distributed among   No           Grant annually 
Grant        areas with    EMAs according to                declines to    
                500,000 or    each EMA's                       98%, 95%, 92%, 
                more in       proportion of ELCs               and 89% of the 
                population    relative to all                  base year      
                and with more EMAs.                            grant,         
                than 2,000                                     respectively.c 
                reported AIDS                                  In the fifth   
                cases in the                                   and all        
                most recent 5                                  subsequent     
                calendar                                       years, EMA     
                yearsb                                         receives 85%   
                                                               of base year   
                                                               grant. The     
                                                               funds          
                                                               necessary to   
                                                               meet the       
                                                               hold-harmless  
                                                               requirement    
                                                               are deducted   
                                                               from funds     
                                                               available for  
                                                               supplemental   
                                                               grants under   
                                                               Title I.d      
Title II     States and    Eighty percent of   For states   Grant declines 
Base Grant   territoriese  base grant funding  with fewer   by 1% per year 
                              divided among       than 90      from the       
                              states/territories  ELCs,        fiscal year    
                              according to each   $200,000;    2000 grant. In 
                              grantee's           states with  fifth year,    
                              proportion of all   90 or more   grant is 95%   
                              ELCs. Twenty        ELCs,        of 2000 grant. 
                              percent of base     $500,000;    
                              grant funding       for          
                              divided among       territories, 
                              states/territories  $50,000      
                              according to each                
                              grantee's ELCs                   
                              located outside the              
                              EMAs within the                  
                              state's/territory's              
                              borders relative to              
                              such ELCs in all                 
                              states/territories.              
Title II     States and    Distributed         No           Grant declines 
ADAP Base    certain       according to each                by 1% per year 
Grant        territoriesf  grantee's                        from the       
                              proportion of all                fiscal year    
                              ELCs.                            2000 grant. In 
                                                               fifth year     
                                                               grant is 95%   
                                                               of 2000 grant. 
Title II     States and    Distributed         No           No             
ADAP Severe  certain       according to each                
Need Grantg  territoriesf  grantee's                        
                with a severe proportion of all                
                need for a    ELCs: grantees must              
                grant to      agree to match 25                
                increase      percent of their                 
                access to     severe need grant                
                medications   and not to impose                
                              eligibility                      
                              requirements                     
                              stricter than those              
                              in place on January              
                              1, 2000.                         
Title II     States and    Funds are divided   Minimum of   No             
Emerging     territories   into two tiers: 50% $5 million   
Communities  with          distributed among   for each     
Grant        metropolitan  communities with    tier         
                areas that    1,000-1,999 AIDS                 
                are not       cases, and 50%                   
                eligible for  distributed among                
                Title I, and  communities with                 
                that have     500-999 AIDS cases.              
                500-1,999     Funding is                       
                reported AIDS distributed                      
                cases in the  according to each                
                most recent 5 community's                      
                calendar      proportion of AIDS               
                years         cases (reported in               
                              the most recent 5                
                              calendar years) in               
                              Emerging                         
                              Communities within               
                              the tier.                        

Source: HRSA.

Notes: HRSA has also awarded Minority AIDS Initiative grants to EMAs,
states, and territories. HRSA characterizes Minority AIDS Initiative
grants to EMAs as Title I grants and Minority AIDS Initiative grants to
states and territories as Title II grants. These funds are allocated by
formula. Title I funds have been used for grants to EMAs with greater than
zero reported nonwhite AIDS cases in the most recent 2 calendar years. The
funds are distributed among all EMAs according to each EMA's proportion of
nonwhite AIDS cases reported over the most recent 2 calendar years. Title
II funds have been used for grants to states and territories with greater
than zero reported nonwhite AIDS cases in the most recent 2 calendar
years. The funds are distributed among all grantees according to each
grantee's proportion of nonwhite AIDS cases reported over the most recent
2 calendar years. There are no minimum-grant or hold-harmless provisions
for these grants.

aIf the distribution formula would otherwise result in a funding decrease
from a prior year, a hold-harmless provision may be triggered to mitigate
the decrease in funding.

bA grandfather clause added in 1996 provides that areas eligible at that
time continue to be eligible even if they no longer meet the eligibility
critieria.

cThe base year is the fiscal year prior to that in which the EMA first
becomes eligible for hold-harmless funding.

dTitle I also includes supplemental grants, which are awarded to EMAs
using a competitive application process based on the demonstration of
severe need and other criteria.

eIn addition to the 50 states, Title II base grants are authorized for the
District of Columbia, the Commonwealth of Puerto Rico, Guam, the Virgin
Islands, American Samoa, the Commonwealth of the Northern Mariana Islands,
the Federated States of Micronesia, the Republic of Palau, and the
Republic of the Marshall Islands.

fIn addition to the 50 states, these grants are authorized for the
District of Columbia, the Commonwealth of Puerto Rico, Guam, and the
Virgin Islands.

gFunding for Severe Need grants may be reduced to maintain funding for
some states under a Title II hold-harmless provision. Severe Need grants
are funded by setting aside 3 percent of the funds earmarked specifically
for ADAPs.

Metropolitan Statistical Areas

In determining a metropolitan area's eligibility for Title I funding and
for purposes of defining areas served under Title I, the CARE Act uses the
OMB 1993 definitions of MSAs. OMB's 1993 definitions were based on
applying OMB's 1990 standards for defining an MSA to data from the 1990
census. OMB's standards create a metropolitan classification scheme that
includes rules for determining which counties (the basic building block of
MSAs) would be designated as the central counties of metropolitan areas
and which outlying counties would be associated with particular central
counties. The 1996 CARE Act amendments froze the metropolitan areas to
those specified in the 1993 OMB definitions. 22

HIV Case Counts

The 2000 amendments provided for HIV case counts to be incorporated in the
Title I and Title II funding formulas as early as fiscal year 2005 if such
data were available and deemed "sufficiently accurate and reliable" by the
Secretary of Health and Human Services. 23 They also required that HIV
data be used no later than the beginning of fiscal year 2007. In June 2004
the Secretary of Health and Human Services determined that HIV data were
not yet ready to be used for the purposes of distributing formula funding
under Title I and Title II of the CARE Act. The Secretary cited a 2004 IOM
report, which identified several limitations in the ability of states to
provide adequate and reliable HIV case counts for use in distributing CARE
Act grants. 24

HOPWA

HOPWA is the only federal program dedicated to providing housing
assistance to persons living with HIV/AIDS and their families. Funding
under HOPWA supports a variety of services, including rental assistance
and the acquisition, rehabilitation, and construction of housing units.
HOPWA funds also provide for supportive services, such as health care,
substance abuse treatment, and case management. In fiscal year 2004, $295
million was distributed through HOPWA.

Ninety percent of HOPWA funds are distributed through formula grants to
states, Puerto Rico, and metropolitan areas. The remaining 10 percent of
HOPWA funds are provided through competitive grants to states, Puerto
Rico, local governments, and nonprofit organizations. Formula grants under
HOPWA incorporate cumulative AIDS case counts, rather than an estimate of
persons living with AIDS, such as ELCs as used in the CARE Act.
Seventy-five percent of HOPWA formula funding is awarded through base
grants to EMSAs, which are jurisdictions with more than 500,000 people and
more than 1,500 cumulative AIDS cases, and to states and Puerto Rico that
have more than 1,500 cumulative AIDS cases outside EMSAs. The remaining 25
percent of HOPWA formula funding is awarded through bonus grants for EMSAs
that meet the eligibility threshold but also demonstrate a
higher-than-average per capita incidence of AIDS. These grants are based
on the number of cases in excess of the average AIDS incidence rates of
EMSAs. HUD first used OMB's new MSA definitions in determining EMSAs for
fiscal year 2004 funding.

Results in Brief

CARE Act and HOPWA grants are used for health care, housing assistance,
and a variety of services for people with HIV/AIDS. In fiscal year 2003,
more than half of the approximately $600 million in Title I CARE Act funds
were allocated by grantees for health care services such as outpatient
care and home health services, and over two-thirds of the approximately $1
billion in Title II funds were allocated by states and territories for
medications. Over three-quarters of the approximately $194 million in
Title III fiscal year 2002 funds were allocated for health care services.
In fiscal year 2003, about $68 million in Title IV grants was provided for
health care and support services for children, youth, and women with
HIV/AIDS and their families. Also in fiscal year 2003, about $74 million
in funding was provided in total for dental programs, projects that
support innovative models of HIV/AIDS care, and AIDS Education and
Training Centers for health care providers. HOPWA funds were used for a
variety of housing-related expenses, such as rental assistance, and
support services. In fiscal year 2003, two-thirds of the approximately
$249 million in HOPWA funds were used for direct housing costs, such as
rental assistance, for people with HIV/AIDS and their families.

Multiple provisions in the CARE Act and HOPWA grant funding formulas
result in funding not being distributed according to the current
distribution of the disease. Grantees do not receive the same level of
CARE Act or HOPWA funding per person living with AIDS because various
formula provisions affect the proportional allocation of funding.

           o  We found that both the CARE Act and HOPWA use measures of AIDS
           cases that do not accurately reflect the number of persons living
           with AIDS. Some CARE Act grants and HOPWA base grant funding are
           based on case counts that could include deceased cases because the
           eligibility and allocations are determined using cumulative case
           counts. In addition, the CARE Act's use of ELCs, which are
           determined using the most recent 10 years of reported AIDS cases,
           to distribute the majority of formula funding does not take into
           account that many AIDS patients now live longer than 10 years
           after their disease is reported.
           o  We found that certain CARE Act Title I and II provisions
           related to metropolitan areas result in variability in the amounts
           of funding per ELC among grantees. For instance, the counting of
           ELCs within EMAs once for determining Title I base grants and once
           again for determining Title II base grants results in states with
           a higher proportion of ELCs in EMAs and Puerto Rico, which has a
           similar percentage, receiving more total Title I and Title II
           funding per ELC than states with no EMA or with comparatively few
           ELCs located in EMAs. Also, the division of Emerging Communities
           into two tiers based on their numbers of reported AIDS cases in
           the past 5 years leads to funding disparities among grantees. This
           divergence occurs because funding is divided equally between the
           two tiers regardless of the number of communities or the number of
           reported AIDS cases in each tier. In fiscal year 2004, the 4
           communities in the first tier received $1,052 per reported case
           while the 25 communities in the second tier received $313 per
           reported case.
           o  We found that because of CARE Act hold-harmless provisions
           under Titles I and II and the grandfather clause for EMAs under
           Title I, the funding of certain grantees is protected. For
           example, the CARE Act Title I hold-harmless provision results in
           the San Francisco EMA's funding being based in part on deceased
           cases in the EMA in 1995. In addition, a Title II hold-harmless
           provision, which has had little effect thus far, has the potential
           to reduce the amount of funding to grantees with severe need for
           drug treatment funds because the hold-harmless provision is funded
           from amounts set aside for ADAP Severe Need grants. The Title I
           grandfather clause protected the funding of more than half of
           EMAs.

           The Ryan White CARE Act Amendments of 2000 required the use of
           HIV/AIDS case counts in the distribution of formula grants not
           later than fiscal year 2007. If case counts from HIV-reporting
           systems had been used along with a measure of the number of
           persons living with AIDS in distributing fiscal year 2004 CARE Act
           and HOPWA grants, funding would have shifted among jurisdictions.
           Although CARE Act and HOPWA grantees have established HIV
           case-reporting systems, differences between these systems-in their
           maturity and reporting methods, for instance-would have affected
           the distribution of CARE Act and HOPWA funds based on HIV/AIDS
           case counts. Recently established HIV-reporting systems might not
           have captured an accurate count of a grantee's HIV cases in part
           because cases diagnosed prior to the establishment of the
           reporting system might not have been reported and entered into the
           system. Also, because CDC does not accept case reports that are
           reported using a code rather than a person's name to protect their
           anonymity, those states with code-based systems would not have had
           their HIV cases counted when funding distributions were made.
           Accordingly, we developed two approaches to assess the effect of
           using the HIV case counts, as they currently exist, on CARE Act
           and HOPWA formula grants. While the extent to which funding may
           have shifted cannot be determined given the different methods
           jurisdictions use to identify HIV cases, we think these approaches
           are informative given the required corporation of HIV cases into
           CARE Act funding formulas. Using these approaches, we found that
           up to 13 percent of CARE Act formula funding would have shifted
           among grantees if HIV cases were included in the funding formulas
           and the hold-harmless provisions analyzed and minimum-grant
           provision were maintained. Larger changes for individual grantees
           would have occurred with some grantees more than doubling their
           funding. Grantees in the South and Midwest would generally have
           received more funding from using HIV cases in funding formulas.
           However, there would have been grantees that would have received
           increased funding and grantees that would have received decreased
           funding in every region of the country. If, in addition to using
           HIV data, the hold-harmless provisions we analyzed and
           minimum-grant provisions were eliminated, the redistribution of
           program funds would have been more dramatic. Up to 24 percent of
           funding would have shifted. HOPWA base funding would also have
           shifted if HIV and living AIDS cases were used to distribute
           funding. In fiscal year 2004, up to 15 percent of HOPWA base
           funding would have shifted among grantees, with six grantees more
           than doubling their funding. Differences in HIV case-reporting
           systems would affect the distribution of funding, and we found
           that funding would have tended to shift to jurisdictions with
           older HIV-reporting systems. Jurisdictions with older
           HIV-reporting systems tend to have more reported HIV cases
           compared with their number of AIDS cases than do jurisdictions
           with newer reporting systems.

           If Congress wishes CARE Act and HOPWA funding to more closely
           reflect the distribution of persons living with AIDS, it should
           take actions that lead to more-comparable funding per case by
           revising the funding formulas. In accordance with achieving
           more-comparable funding per AIDS case, we raise a number of
           matters for consideration when Congress reviews the CARE Act and
           HOPWA.

           We provided a draft of this report to HHS and HUD. HHS and HUD
           generally agreed with our identification of issues in the funding
           formulas. While HHS also generally agreed with our matters for
           congressional consideration, it expressed concern that our
           discussion of the Title I grandfather provision in the CARE Act
           could be interpreted as suggesting that the metropolitan areas
           that continue to receive grants because of this provision need not
           be funded. However, these areas could still receive funding
           through their respective states or territories, which receive
           funds under Title II. HUD concurred with our matter for
           congressional consideration that HOPWA formula grant eligibility
           and base grant funding be based on a measure of living AIDS cases.

CARE Act and HOPWA Funds Allocated for Health Care, Housing Assistance,
and a Variety of Other Services

The CARE Act and HOPWA grants fund a variety of treatment and support
services for people with HIV/AIDS. For fiscal year 2003, Title I grantees
allocated more than half of the approximately $600 million in Title I
grants for health care services such as outpatient care and home health
care, and over 70 percent of the approximately $1 billion in Title II
funds were allocated for medications. Almost 80 percent of the
approximately $194 million in Title III fiscal year 2002 funds were
allocated for health care services such as physician office visits and HIV
counseling and testing. 25 In fiscal year 2003, there was also about $68
million in funding for Title IV grantees and about $74 million for other
programs, such as Special Projects of National Significance. Two-thirds of
the approximately $249 million in HOPWA fiscal year 2003 funds were used
to assist with housing costs for people with HIV/AIDS and their families.

More Than Half of Title I Fiscal Year 2003 Funding Was Allocated for
Health Care Services

For fiscal year 2003, HRSA provided about $600 million in grants to EMAs
under Title I of the CARE Act to support services for people with
HIV/AIDS. Grantees allocated the largest portion of these funds, about 52
percent, for health care services such as outpatient care, home health
care, rehabilitation care, and medications. About 12 percent of these
Title I health care services funds were allocated for substance abuse
treatment and counseling services. For the same year, Title I grantees
allocated about 36 percent of those funds for case management and support
services. Support services include child care, client advocacy, and
emergency financial assistance, among others. The remaining 12 percent of
Title I funding was allocated for administration, planning councils, and
program support. 26 (See fig. 2.)

Figure 2: Allocation of CARE Act Title I Funds, Fiscal Year 2003

Note: About $600 million was allocated under Title I.

Over Two-thirds of Title II Fiscal Year 2003 Funding Was Allocated for
Medications

HRSA provided approximately $1 billion to states and territories under
Title II in fiscal year 2003. Title II grantees allocated the majority of
these funds, about 71 percent, for medications, which includes ADAP
medications, non-ADAP medications, and pharmacy assistance for CARE Act
clients. Ten percent of Title II funds were allocated for health care
services, similar to those provided under Title I. Grantees allocated
about 3 percent of Title II health care services funds for substance abuse
treatment services. Case management and support services similar to those
provided under Title I accounted for approximately 10 percent of the Title
II funds. The remainder of Title II funds, about 9 percent, was allocated
for program administration, planning, and evaluation. 27 (See fig. 3.)

Figure 3: Allocation of CARE Act Title II Funds, Fiscal Year 2003

Notes: Approximately $1 billion was allocated under Title II.

aMedications includes ADAP medications, non-ADAP medications, and pharmacy
assistance.

Over Three-quarters of Title III Fiscal Year 2002 Funding Was Allocated
for Health Care Services

Under Title III of the CARE Act, HRSA provided about $194 million in
grants to certain public and nonprofit primary care providers in support
of early intervention services for people with HIV/AIDS for fiscal year
2002. Title III grantees allocated about 79 percent of these funds for
health care services such as physician office visits, HIV counseling and
testing, and employing primary care personnel. Health care services also
included outpatient mental health care and substance abuse treatment.
Title III grantees allocated another 13 percent for other activities,
including case management and HIV patient education. The remaining 8
percent was allocated for administration. 28 (See fig. 4.)

Figure 4: Allocation of CARE Act Title III Funds, Fiscal Year 2002

Note: About $194 million was allocated under Title III.

CARE Act Grants Funded Other Activities in Fiscal Year 2003

Grants made under Title IV of the CARE Act address the specific needs of
women, infants, children, and youth living with HIV/AIDS. The funds cover
primary and specialty medical care, psychosocial services, case
management, and other activities. For fiscal year 2003, HRSA provided
about $68 million for Title IV programs. Other CARE Act programs include
the Special Projects of National Significance Program, funded at about $25
million for fiscal year 2003; the AIDS Education and Training Centers
Program, funded at about $36 million for fiscal year 2003; and the
HIV/AIDS Dental Reimbursement Program and Community-Based Dental
Partnership program funded at nearly $10 million and $3 million
respectively for fiscal year 2003.

Two-thirds of HOPWA Fiscal Year 2003 Funds Were Spent on Housing Costs

For fiscal year 2003, HOPWA grantees spent about $249 million to support
housing services for people with HIV/AIDS. The largest portion of these
funds, about 66 percent, was spent on direct housing costs, such as rental
assistance, and housing facility operating costs. Support services
accounted for 25 percent of the funds. HOPWA-funded support services
include case management, health care, alcohol and drug abuse treatment,
and child care, among others. Housing information services and permanent
housing placement costs accounted for 4 percent of HOPWA funds, while
grant administration was 5 percent of the total. (See fig. 5.)

Figure 5: Allocation of HOPWA Funds, Fiscal Year 2003

Notes: About $249 million was spent under HOPWA.

Multiple Provisions Contribute to Disproportionate Distribution of CARE
Act and HOPWA Formula Funding

Provisions in the CARE Act and HOPWA funding formulas result in a
distribution of funds among grantees that does not reflect the relative
distribution of AIDS cases in these jurisdictions. 29 CARE Act grantees do
not receive the same amount of funding per ELC, and HOPWA grantees do not
receive the same amount of funding per living AIDS case. We found that
provisions affected the proportional allocation of funding as follows: (1)
the AIDS case-count provisions in the CARE Act and HOPWA each result in a
distribution of funding that is not reflective of the distribution of
persons living with AIDS, (2) CARE Act provisions related to metropolitan
areas result in variability in the amounts of funding per ELC among
grantees, (3) the CARE Act hold-harmless provisions and grandfather clause
protect the funding of certain grantees, and (4) the ineligibility of
grantees other than EMSAs for HOPWA bonus funding restricts the
distribution of these funds and limits HUD's ability to fund areas outside
of EMSAs with high rates of new AIDS cases. We also considered the
provision in the 1996 CARE Act amendments that froze the EMA boundaries to
1993 OMB definitions. We found that the boundaries for more than half of
current EMAs would change if OMB's 2004 MSA definitions were adopted for
purposes of CARE Act funding.

CARE Act and HOPWA Grants Are Not Distributed Solely in Proportion to
Number of Persons Living with AIDS

Funds distributed under Title I of the CARE Act are not distributed
proportionally per ELC across EMAs. 30 In fiscal year 2004, the total
funding for all Title I grants to EMAs was about $595 million. If this
funding had been distributed solely by a grantee's proportion of ELCs,
each EMA would have received $2,443 per ELC. However, Title I provisions
affect the grant awards so that funding is not distributed strictly on a
proportional basis, but instead is allocated in part according to the
number of ELCs and in part on other bases, such as the amounts awarded in
a prior year, as reflected in the hold-harmless funding. Total funding for
EMAs also reflects Minority AIDS Initiative grants and supplemental
grants. In fiscal year 2004, total Title I funding for the 51 EMAs ranged
from $2,130 per ELC case in Riverside-San Bernardino to $4,137 in San
Francisco, with an average of $2,380. Excluding San Francisco, West Palm
Beach had the highest Title I funding per ELC at $2,515. Appendix II lists
the EMAs and amounts awarded under Title I for fiscal year 2004.

CARE Act Title II funding is also not distributed proportionally per ELC.
In fiscal year 2004, the total funding for all Title II grants was about
$1.051 billion. If this funding had been distributed solely according to
the proportion of ELCs, each grantee would have received $3,053 per ELC.
However, minimum-award requirements and hold-harmless provisions affect
the distribution of Title II funds. In addition, grants for Emerging
Communities as well as the Minority AIDS Initiative are not determined
proportionally by the number of ELCs. Total Title II funding for fiscal
year 2004 ranged from $2,793 for the District of Columbia to $7,275 for
South Dakota, with an average of $3,559. Appendix III shows the grantees
and amounts awarded under Title II for fiscal year 2004.

HOPWA formula funding is also disproportionate across grantees. In fiscal
year 2004, about $263 million was allocated by formula to 117 grantees.
Seventy-five percent of this funding was distributed according to the
number of cumulative AIDS cases 31 in a jurisdiction and 25 percent was
distributed based on the rate of new AIDS cases in EMSAs. If this funding
had been distributed proportionally by the number of cumulative AIDS cases
across jurisdictions each grantee would have received $306 per cumulative
case. However, 26 grantees received bonus grants that are based on the
rate of new AIDS cases in an EMSA, not the number of cumulative AIDS
cases. Therefore, the actual amounts grantees received ranged from $230
per cumulative AIDS case for 91 grantees to $626 per case in Baton Rouge,
with an average of $260. We also determined how much funding each grantee
received per living AIDS case. 32 We found that grantees received an
average of $573 per living AIDS case, with funding ranging from $387 per
case in Nashville to $1,290 per case in Baton Rouge. These funding
differences are due to the use of cumulative AIDS cases to distribute base
grant funding and because bonus grants are distributed according to the
rate of new cases in EMSAs. 33 Appendix IV identifies the fiscal year 2004
HOPWA formula grantees and award amounts.

Provisions in HOPWA and CARE Act Funding Formulas Incorporate Measures of
AIDS Cases That Do Not Reflect an Accurate Count of Persons Living with
AIDS

HOPWA and the CARE Act both use measurements of AIDS cases that do not
reflect an accurate count of people currently living with AIDS. To
determine eligibility for HOPWA formula grants and to distribute base
funding, allocations are determined using a measure of AIDS cases that is
based on the number of living and deceased AIDS cases reported in the
jurisdiction since the beginning of the AIDS epidemic in 1981. Also,
eligibility and distribution of certain CARE Act grants are based on the
number of reported AIDS cases over either the last 2- or 5-year period, 34
which likely does not reflect all live cases and could include deceased
AIDS cases. In addition, Title I, Title II, and ADAP base grants are
calculated using ELCs, which can underestimate the number of living cases
because many persons with AIDS now live longer than 10 years after their
cases are reported.

HOPWA Grants

Eligibility for HOPWA formula grants is determined by the number of
cumulative AIDS cases in a metropolitan area, state, and Puerto Rico, and
base funding allocations (which represent 75 percent of total HOPWA
formula funding) to grantees are determined by the grantee's proportion of
the total number of cumulative AIDS cases. As we reported in 1995, the use
of cumulative case counts is an inappropriate caseload measure because it
includes all AIDS cases, living and dead, reported to CDC for the
jurisdiction since the beginning of the epidemic in 1981. 35

Because the HOPWA funding formula includes deceased persons, the
distribution of funds does not reflect the current distribution of people
living with AIDS. Using estimates of living AIDS cases obtained from CDC,
we calculated how base funding for grantees would have changed in fiscal
year 2004 if these estimates had been used instead of the cumulative case
counts. Each of the 117 grantees would have received approximately $537
per living AIDS case. We found that 25 grantees received more funding in
fiscal year 2004 using cumulative case counts than they would have
received if the number of living AIDS cases had been used. The additional
funding received by the grantees ranged from approximately $2,000 in San
Jose to $4,020,000 in New York City. Conversely, if the number of living
cases had been used, 92 grantees would have received increased funding.
The funding increases would have ranged from $1,000 in Springfield,
Massachusetts, to $1,120,000 in the District of Columbia. Areas that
receive more funding from the use of cumulative case counts include
jurisdictions in California, Michigan, New Jersey, and New York. (App. V
contains information on funding using cumulative AIDS counts and living
AIDS cases.)

Use of cumulative case counts rather than living cases can lead to areas
with similar numbers of living AIDS cases receiving markedly different
amounts of funding. For example, as of March 31, 2003, Oakland and New
Orleans both reported 3,374 living AIDS cases. 36 However, in fiscal year
2004 Oakland received $221,000 more ($66 more per living AIDS case) in
HOPWA base funding than did New Orleans. Atlanta and Houston also have
similar numbers of living AIDS cases (8,557 and 8,579 respectively).
However, in fiscal year 2004 Houston received $806,000 more ($93 more per
case) in HOPWA base funding than did Atlanta.

CARE Act Grants

The use of cumulative case counts is not limited to the HOPWA program.
Deceased cases can also be included when determining eligibility for CARE
Act funding. Eligibility for Title I funding and Title II Emerging
Communities grants is based on cumulative totals of AIDS cases reported in
the most recent 5-year period, not on the number of ELCs. Funding amounts
for Emerging Communities grants are also determined using the most recent
5 years of reported cases. In addition, HRSA determines eligibility and
funding amounts of Minority AIDS Initiative grants according to the number
of reported AIDS cases in the most recent 2-year period.

The use of the cumulative number of reported cases over a certain period
to determine eligibility and allocate funding results in funding not being
distributed according to the current distribution of the disease. For
example, because Emerging Communities funding is determined by using
5-year cumulative case counts, allocations could be based in part on
deceased cases, that is, people for whom AIDS was reported in the past 5
years but who have since died. In addition, these case counts do not take
into account living cases in which AIDS was diagnosed more than 5 years
earlier. Consequently, 5-year cumulative case counts can substantially
misrepresent the number of AIDS patients in these communities. For
example, while the 5-year cumulative case count in Buffalo for determining
fiscal year 2004 Emerging Communities eligibility and funding was 581
cases, the number of ELCs was 956. Similarly, the 5-year cumulative case
count in Charleston, South Carolina, was 538, but the number of ELCs was
758.

The use of ELCs as provided for in the CARE Act can also lead to
inaccurate estimates of living AIDS cases. Currently, Title I, Title II,
and ADAP base funding, which constitute the majority of formula funding,
are distributed according to ELCs. ELCs are an estimate of living AIDS
cases calculated by applying annual national survival weights to the most
recent 10 years of reported AIDS cases and adding the totals from each
year. This method for estimating cases was first included in the CARE Act
Amendments of 1996. At that time, this approach captured the vast majority
of living AIDS cases. However, some persons with AIDS now live more than
10 years after their case is first reported, and they are not accounted
for by this formula. 37 Thus, like the 2- and 5-year reported case counts,
ELCs can misrepresent the number of living AIDS cases in an area in part
by not taking into account those persons living with AIDS whose cases were
reported more than 10 years earlier. For example, fiscal year 2004 Title I
base funding for the Atlanta EMA was based on 7,589 ELCs, but CDC
estimated that there were 8,560 reported living AIDS cases in the EMA. 38
Similarly, funding for the Seattle EMA was based on 2,468 ELCs while CDC
estimated that there were 3,273 reported living cases. 39

CARE Act Funding Provisions for Metropolitan Areas Result in
Disproportionate Funding

The counting of ELCs within EMAs once to determine the amount of the base
grant under Title I and once again to determine the amount of the Title II
base grant results in states with EMAs and Puerto Rico receiving more
total Title I and Title II funding per ELC than states without EMAs. 40 In
addition, the formula for awarding Title II Emerging Communities grants
results in different levels of funding per AIDS case across grantees.

Counting ELCs within EMAs Twice Results in Disproportionate Funding per
ELC across States and Puerto Rico

When total Title I and Title II funding is considered, states with EMAs
and Puerto Rico receive more funding per ELC than states without EMAs
because cases within EMAs are counted twice, once in connection with Title
I base grants and once for Title II base grants. Eighty percent of Title
II base grants is determined by the total number of ELCs in the state or
territory. The remaining 20 percent is based on the number of ELCs in each
jurisdiction outside of any EMA. This 80/20 split was established by the
1996 CARE Act amendments to address the concern that grantees with EMAs
received more total Title I and Title II funding per case than grantees
without EMAs. However, even with the 80/20 split, states with EMAs and
Puerto Rico receive more total Title I and Title II funding per ELC than
states without EMAs. States without EMAs receive no funding under Title I,
and thus, when total Title I and Title II funds are considered, states
with EMAs and Puerto Rico receive more funding per ELC. 41 Appendix VI
shows the combined Title I and Title II fiscal year 2004 funding received
by each state and Puerto Rico.

Table 3 illustrates the effect of counting EMA cases twice by comparing
the relationship between the percentage of a state's and Puerto Rico's
ELCs that are within EMAs and the amount of total Title I and Title II
funding they receive per ELC. Table 3 shows that as the percentage of a
state's or Puerto Rico's ELCs within EMAs increases, the total Title I and
II funding per ELC also increases. For example, states with no ELCs in
EMAs received on average $3,592 per ELC. States with 75 percent or more of
their cases in EMAs and Puerto Rico 42 received on average $4,955 per ELC,
or 38 percent more funding than states with no EMA. If the total Title I
and Title II funding had been distributed proportionally per ELC among all
states and Puerto Rico, each grantee would have received $4,782 per ELC.

Table 3: Relationship between ELCs in EMAs and Total CARE Act Title I and
II Funding per ELC, Fiscal Year 2004

Percentage of states' and Puerto Rico's ELCs in   Average funding per ELCa 
EMAs                                              
None                                                                $3,592 
Less than 50 percent                                                 3,954 
50 to 75 percent                                                     4,717 
More than 75 percent                                                 4,955 

Source: GAO analysis of HRSA data.

aWe excluded from our analyses the nine states that received the minimum
Title II base grant awards. Under Title II, states with fewer than 90
cases receive no less than $200,000 in Title II base grant and states with
90 or more cases receive at least $500,000.

The effect of counting EMA cases twice is that grantees with similar
numbers of ELCs can receive different levels of combined Title I and Title
II funding. For example, for fiscal year 2004 funding, Connecticut had
5,363 ELCs while South Carolina had 5,563 ELCs. However, Connecticut had
two EMAs that accounted for 91.3 percent of its ELCs while South Carolina
had none. Connecticut received $26,797,308 ($4,997 per ELC) in combined
Title I and Title II funding while South Carolina, with 200 more cases,
received $20,705,328 ($3,722 per ELC). Connecticut received 29 percent
more funding than South Carolina, a difference of $6,091,980, or $1,275
per ELC. (See app. VI.)

The Two-tiered Division of Emerging Communities Results in Funding
Disparities Among Metropolitan Areas

The two-tiered division of Emerging Communities results in disparities in
funding among metropolitan areas. Title II provides for a minimum of $10
million to states with metropolitan areas that have 500 to 1,999 AIDS
cases reported in the last 5 calendar years but do not qualify for funding
under Title I as EMAs. 43 The funding is equally split so that half the
funding is divided among the first tier of communities with 500 to 999
reported cases in the most recent 5 calendar years while the other half is
for a second tier of communities with 1,000 to 1,999 reported cases in
that period. The funding is then allocated within each tier by the
proportion of reported cases in the most recent 5 calendar years in each
community. The two tiers and the 50/50 split were meant to ensure that a
significant portion of the Emerging Communities funding was allocated to
the communities with the largest number of new cases.

In fiscal year 2004, the two-tiered structure of Emerging Communities
funding led to large differences in funding per reported AIDS case in the
last 5 calendar years among the Emerging Communities because the total
number of AIDS cases in each tier was not equal. Twenty-nine communities
qualified for Emerging Communities funds in fiscal year 2004. Four of
these communities had 1,000 to 1,999 reported AIDS cases in the last 5
calendar years and 25 communities had 500 to 999 cases. This distribution
meant that the 4 communities with a total of 4,754 reported cases in the
last 5 calendar years split $5 million while the remaining 25 communities
with a total of 15,994 reported cases in the last 5 calendar years also
split $5 million. These case counts resulted in the 4 communities
receiving $1,052 per reported case while the other 25 received $313 per
reported case. These 4 communities received 236 percent more funding per
reported case than the other 25. If the total $10 million funding for
Emerging Communities grants had been distributed equally per reported case
among the communities, each would have received $482 per reported case.
Table 4 lists the 29 Emerging Communities along with their reported AIDS
case counts over the most recent 5 years and their funding.

Table 4: Title II Emerging Communities in Fiscal Year 2004

Emerging Community                    AIDS cases      Emerging Communities 
                                    reported in the     funding per AIDS case 
                                      most recent 5      reported in the most 
                                     calendar years   recent 5 calendar years 
Memphis, Tenn.                             1,588                    $1,052 
Nashville, Tenn.                           1,123                     1,052 
Baton Rouge, La.                           1,038                     1,052 
Indianapolis, Ind.                         1,005                     1,052 
Columbia, S.C.                               972                       313 
Charlotte, N.C.                              875                       313 
Wilmington, Del.                             801                       313 
Richmond, Va.                                783                       313 
Raleigh-Durham-Chapel Hill, N.C.             775                       313 
Jackson, Miss.                               722                       313 
Louisville, Ky.                              705                       313 
Rochester, N.Y.                              681                       313 
Fort Pierce-Port St. Lucie, Fla.             636                       313 
Greensboro-Winston-Salem, N.C.               617                       313 
Birmingham, Ala.                             615                       313 
Oklahoma City, Okla.                         608                       313 
Pittsburgh, Pa.                              602                       313 
Springfield, Mass.                           588                       313 
Monmouth-Ocean, N.J.                         582                       313 
Buffalo-Niagara Falls, N.Y.                  581                       313 
Greenville, S.C.                             560                       313 
Columbus, Ohio                               558                       313 
Milwaukee, Wis.                              558                       313 
Salt Lake City, Utah                         555                       313 
Sarasota, Fla.                               539                       313 
Charleston, S.C.                             538                       313 
Cincinnati, Ohio                             517                       313 
Daytona Beach, Fla.                          514                       313 
Providence, R.I.                             512                       313 
Total                                     20,748 

Source: GAO analysis of HRSA data.

Note: Emerging Communities are metropolitan areas not eligible for Title I
grants and that have 500-1,999 reported AIDS cases in the most recent 5
calendar years. The 5 most recent calendar years are 1998-2002.

Similar to the counting of ELCs in EMAs for both Title I and Title II base
grant funding, AIDS cases reported in the past 5 calendar years in
Emerging Communities are counted more than once for determining Title II
funding. For example, these cases are counted once for determining Title
II base funding and again for Emerging Communities grants. Title II
grantees with Emerging Communities receive an average of $3,443 per ELC
while grantees without an Emerging Community receive about $3,089. 44 The
Emerging Communities funding accounted for about $125 per ELC of this
difference. Other Title II funds that are also not distributed
proportionally by the number of ELCs, such as the Minority AIDS Initiative
grants, account for the rest of the difference. 45

Hold-harmless Provisions and Grandfather Clause Protect Funding of Certain
CARE Act Grantees

Titles I and II of the CARE Act both contain provisions that protect
certain grantees' funding levels. Title I has a hold-harmless provision
that guarantees that the Title I base grant to an EMA will be at least as
large as a statutorily specified percentage of a previous year's funding.
The Title I hold-harmless provision has primarily protected the funding of
one EMA. Title I also contains a grandfather clause that has resulted in a
large number of EMAs maintaining their eligibility for grants despite no
longer meeting the eligibility criteria. Title II has a hold-harmless
provision that ensures that the total of Title II and ADAP base grants
awarded to a grantee will be at least as large as the total of these
grants a grantee received the previous year. This provision has the
potential of reducing the amount of funding to grantees that had
demonstrated severe need for drug treatment funds because it is funded out
of amounts that would otherwise be used for that purpose.

One EMA Has Been the Primary Recipient of Title I Hold-harmless Funding

The San Francisco EMA has been the primary recipient of Title I
hold-harmless funding. An EMA's base funding is determined according to
its proportion of ELCs. The hold-harmless provision guarantees each EMA a
statutorily specified percentage of the base grant it received in a
previous year regardless of how much its proportion of the number of ELCs
in all EMAs may have decreased in the current year. 46 If an EMA qualifies
for hold-harmless funding, that amount is added to the base funding and
distributed together as the base grant. In fiscal year 2004, the San
Francisco EMA received $7,358,239 in hold-harmless funding, or 91.6
percent of the hold-harmless funding that was distributed. 47 The second
largest recipient was Kansas City, which received $134,485, or 1.7 percent
of the hold-harmless funding under Title I. Table 5 lists the EMAs that
received hold-harmless funding in fiscal year 2004. 48

Table 5: Title I Hold-harmless Funding, Fiscal Year 2004

EMA                           Hold-harmless    Percent of Hold-harmless   Base Hold-harmless 
                                    funding hold-harmless   funding per  grant  as a percent 
                                                  funding           ELC    per of base grant 
                                                                          ELCa 
San Francisco, Calif.            $7,358,239         91.6%        $1,020 $2,241         45.5% 
Kansas City, Mo.                    134,485           1.7           104  1,325           7.8 
Santa Rosa, Calif.                   22,614           0.3            47  1,268           3.7 
Sacramento, Calif.                   36,456           0.5            29  1,251           2.3 
Minneapolis-St. Paul, Minn.          33,770           0.4            27  1,248           2.1 
Bergen-Passaic, N.J.                 55,288           0.7            26  1,248           2.1 
Jersey City, N.J.                    58,310           0.7            24  1,245           1.9 
Oakland, Calif.                      50,744           0.6            18  1,239           1.4 
New Haven, Conn.                     42,573           0.5            14  1,236           1.2 
Tampa-St. Petersburg, Fla.           44,908           0.6            12  1,233           0.9 
San Jose, Calif.                     12,097           0.2            11  1,232           0.9 
Boston, Mass.                        60,284           0.8            10  1,231           0.8 
Nassau-Suffolk, N.Y.                 21,212           0.3             8  1,230           0.7 
Middlesex-Somerset-Hunterdon,         8,315           0.1             7  1,228           0.5 
N.J.                                                                           
Jacksonville, Fla.                   12,825           0.2             6  1,228           0.5 
San Juan, P.R.                       41,011           0.5             6  1,228           0.5 
Seattle, Wash.                        9,844           0.1             4  1,225           0.3 
Denver, Colo.                         6,745           0.1             3  1,225           0.3 
Cleveland, Ohio                       4,616           0.1             3  1,224           0.2 
West Palm Beach, Fla.                 8,523           0.1             2  1,224           0.2 
Newark, N.J.                         10,975           0.1             2  1,223           0.1 
All Other EMAs                            0             0             0  1,221           0.0 
Total                           $8,033,563b       100.0%b                      

Source: GAO analysis of HRSA data.

Notes: An EMA's base funding is determined according to its proportion of
ELCs. If an EMA qualifies for hold-harmless funding, that amount is added
to the base funding and distributed together as the base grant.

aThis amount was calculated by dividing the base grant, including any
hold-harmless funding, received by each EMA by the number of ELCs in the
EMA.

bIndividual entries do not sum to total because of rounding.

The effect of the hold-harmless provision varies among the EMAs that
receive hold-harmless funding, but it can be substantial. In order to
place hold-harmless funding in perspective, it is helpful to consider how
much of an EMA's Title I base grant was made up of hold-harmless funding.
EMAs that did not receive hold-harmless funding received approximately
$1,221 in base grant funding per ELC in fiscal year 2004. Fiscal year 2004
base grant funding per ELC in EMAs that received hold-harmless funding
ranged from $1,223 (Newark) to $2,241 (San Francisco). Thus, the San
Francisco EMA received $1,020 more in base grant funding per ELC than did
EMAs that did not receive hold-harmless funding. This hold-harmless
funding represents approximately 46 percent of San Francisco's base grant.
Because of its hold-harmless funding, San Francisco, which had 7,216 ELCs
in fiscal year 2004, received a base grant equivalent to what an EMA with
approximately 13,245 ELCs (84 percent more) would have received. Kansas
City, the second largest hold-harmless grantee, received about what an EMA
with 9 percent more ELCs would have received.

Forty-eight of the 51 EMAs would have received more funding if there had
been no hold-harmless provision and if the $8 million that was actually
used for hold-harmless funding had been distributed in the same
proportions as the supplemental grants. 49 Although 21 EMAs received
hold-harmless funding in fiscal year 2004, only 3 (San Francisco, Kansas
City, and Santa Rosa) received more funding because of the hold-harmless
provision than they would have received through supplemental grants in the
absence of the hold-harmless provision. Without the hold-harmless funding,
San Francisco would have received $960 less per ELC, Kansas City $70 less,
and Santa Rosa $15 less.

In fiscal year 2004 the San Francisco EMA was guaranteed to receive 89
percent of its fiscal year 2000 Title I base grant under the hold-harmless
provision. However, the amount of San Francisco's 2000 Title I base grant
had been determined by formulas specified in the CARE Act Amendments of
1996, which guaranteed EMAs 95 percent of their 1995 base grant in fiscal
year 2000. 50 San Francisco was the only EMA to qualify for hold-harmless
funding in 2000 because it was the only EMA that would have received less
than 95 percent of its fiscal year 1995 base grant. Taken together, the
hold-harmless provisions mean that in fiscal year 2004 San Francisco was
guaranteed approximately 85 percent of its fiscal year 1995 base grant of
$19,126,679. 51 Prior to the CARE Act Amendments of 1996, funding was
distributed among EMAs on the basis of the cumulative count of diagnosed
AIDS cases (that is, all cases reported in an EMA both living and deceased
since the beginning of the epidemic in 1981). Because San Francisco's
Title I funding reflects the application of hold-harmless provisions under
the 1996 amendments, as well as under current law, San Francisco's Title I
base grant is determined in part by the number of deceased cases in the
San Francisco EMA as of 1995.

Grandfathering Maintains Eligibility for EMAs That No Longer Meet Certain
Eligibility Criteria

More than half of the EMAs received Title I funding in fiscal year 2004
even though they were below Title I eligibility thresholds. 52 The
eligibility of these EMAs was protected based on a CARE Act grandfather
clause. Under a grandfather clause established by the CARE Act Amendments
of 1996, metropolitan areas eligible for funding for fiscal year 1996
remain eligible for Title I funding even if the number of reported cases
in the most recent 5 calendar years drops below the statutory threshold.
We found that in fiscal year 2004, 29 of the 51 EMAs did not meet the
eligibility threshold of more than 2,000 reported AIDS cases during the
most recent 5 calendar years but nonetheless retained their status as EMAs
(see table 6). The number of reported AIDS cases in the most recent 5
calendar years in the 29 EMAs ranged from 223 to 1,941. Title I funding
awarded to these 29 EMAs was about $116 million, or approximately 20
percent of the total Title I funding.

Table 6: Grandfathered EMAs, Fiscal Year 2004

EMA                                     Number of AIDS cases Total Title I 
                                           reported in the most       funding 
                                        recent 5 calendar years 
Riverside-San Bernardino, Calif.                       1,941    $6,823,183 
New Haven, Conn.                                       1,717     7,069,348 
Oakland, Calif.                                        1,633     6,611,607 
Nassau-Suffolk, N.Y.                                   1,560     5,951,789 
Norfolk, Va.                                           1,502     4,820,201 
Seattle, Wash.                                         1,459     5,842,615 
Jacksonville, Fla.                                     1,423     4,863,093 
Orange County, Calif.                                  1,422     5,233,329 
St. Louis, Mo.                                         1,247     4,371,154 
Jersey City, N.J.                                      1,226     5,884,194 
Las Vegas, Nev.                                        1,182     4,473,401 
Denver, Colo.                                          1,167     4,529,097 
Austin, Tex.                                           1,149     3,800,250 
Bergen-Passaic, N.J.                                   1,067     4,814,704 
Hartford, Conn.                                        1,059     4,552,237 
San Antonio, Tex.                                      1,034     3,833,443 
Cleveland, Ohio                                          970     3,486,936 
Portland, Oreg.                                          937     3,567,475 
Fort Worth, Tex.                                         854     3,373,450 
Kansas City, Mo.                                         822     3,240,813 
Minneapolis, Minn.                                       794     3,093,915 
Sacramento, Calif.                                       717     2,968,051 
Ponce, P.R.                                              710     2,718,331 
Middlesex-Somerset-Hunterdon, N.J.                       682     2,723,697 
San Jose, Calif.                                         656     2,656,550 
Caguas, P.R.                                             411     1,816,647 
Dutchess County, N.Y.                                    255     1,231,242 
Vineland-Millville-Bridgeton, N.J.                       238       847,898 
Santa Rosa, Calif.                                       223     1,107,428 
Total                                                         $116,306,348 

Source: GAO analysis of CDC and HRSA data.

Note: The 5 most recent calendar years are 1998-2002.

The number of EMAs ineligible for Title I funds in the absence of the
grandfather clause reflects the combination of the decline in the number
of new AIDS cases following the advent of more effective therapies and the
more restrictive eligibility standards adopted in the CARE Act Amendments
of 1996. 53 No metropolitan areas have become eligible for Title I funding
since 1999, when Las Vegas and Norfolk received their initial funding,
because no additional metropolitan areas have reported enough new cases to
meet the AIDS case-count-eligibility threshold. This decline in the number
of new cases reflects the general pattern of AIDS case counts in the
country. While the number of people living with AIDS has been increasing
as persons with AIDS live longer, the number of new AIDS cases reported
each year throughout the country decreased from about 1993 until about
1999 and has since leveled off. In addition, six of the EMAs not meeting
the current eligibility threshold became eligible on the basis of their
case rates, under the 1990 thresholds, rather than their number of cases.
These include Caguas, Dutchess County, Santa Rosa, and
Vineland-Millville-Bridgeton, the four EMAs with the fewest reported
cases. In addition, the Jersey City and Ponce EMAs also became eligible on
the basis of their case rates.

As discussed earlier, some metropolitan areas are designated as Emerging
Communities under Title II because their numbers of reported AIDS cases in
the most recent 5 calendar years are not large enough to make them
eligible for Title I funding as EMAs. However, some Emerging Communities
had more reported AIDS cases in the last 5 years than some EMAs that were
eligible for Title I funding because of the grandfather clause. 54 For
example, for fiscal year 2004 Memphis, a designated Emerging Community,
had 1,588 reported AIDS cases during the most recent 5 calendar years,
which is more than the number of cases reported in 26 EMAs. The overall
effect is that Emerging Communities received less funding than EMAs with
comparable numbers of reported AIDS cases in the most recent 5 calendar
years. For example, Baton Rouge, with 1,038 reported cases, received
$1,091,976 in Emerging Communities funding while the San Antonio EMA, with
1,034 reported cases, received $3,833,443 in Title I funding.

Title II Hold-harmless Funding Could Diminish ADAP Severe Need Grants in
the Future

A Title II hold-harmless provision established by the CARE Act Amendments
of 2000 could diminish ADAP Severe Need grant amounts in the future
because the hold-harmless payments and the grants are funded from the same
3 percent set-aside of Title II funds available for drug treatment
programs. If larger amounts are needed to meet this hold-harmless
provision in the future, grantees that have demonstrated a severe need for
drug treatment funds could get less than the amounts they would otherwise
receive. 55

Fiscal year 2004 was the first time that any grantees triggered the Title
II hold-harmless provision funded with amounts that would otherwise be
used for Severe Need grants. Severe Need grants are funded with a 3
percent set-aside of the funds appropriated specifically for ADAPs. The
Title II hold-harmless provision, also funded by the 3 percent set-aside
for Severe Need grants, guarantees that the total of Title II and ADAP
base grants made to a grantee will be at least as large as the total the
previous year. 56 Eight states became eligible for this hold-harmless
funding in fiscal year 2004. In 2004, the 3 percent set-aside for Severe
Need grants was $22.5 million. Of these funds, $1.6 million, or 7 percent,
was used to provide this Title II hold-harmless protection. (See table 7.)
The remaining $20.8 million, or 93 percent of the set-aside amount, was
distributed in Severe Need grants.

Table 7: States That Received Title II Hold-harmless Funding from Severe
Need Set-aside, Fiscal Year 2004

State        Hold-harmless amount 
Arkansas                  $23,705 
Kansas                     22,168 
New Mexico                 55,171 
North Dakota                1,820 
Oklahoma                   96,423 
Tennessee               1,300,502 
Utah                      119,695 
Vermont                       128 
Total                  $1,619,612 

Source: HRSA.

The potential exists for this Title II hold-harmless provision to diminish
the size of Severe Need grants further in the future if larger amounts are
needed to fund this hold-harmless protection. The total amount of Severe
Need grant funds available in fiscal year 2004 to distribute among the
eligible grantees was less than it would have been without the
hold-harmless payments. However, in fiscal year 2004 not all 25 of the
Title II grantees eligible for Severe Need grants made the required match.
Consequently, the Severe Need grants were not as small as they would
otherwise have been because of the application of the hold-harmless
provision. In future years, if all of the eligible Title II grantees make
the match, and if there are also grantees that qualify to receive
hold-harmless funds under this provision, grantees with severe need for
ADAP funding would get less than the amounts they would otherwise receive.

HOPWA Provision Restricts Bonus Grant Eligibility for Some Grantees

The structure of the HOPWA program restricts states and Puerto Rico from
receiving HOPWA bonus grant funding for areas outside EMSAs. 57 Bonus
grants, which totaled about $66 million in fiscal year 2004, are awarded
only to the EMSAs in which the AIDS epidemic is spreading most rapidly. 58
In fiscal year 2004, EMSAs with more than 19.5 new AIDS cases per 100,000
people over the past year qualified for bonus grants. In fiscal year 2004,
26 EMSAs qualified for bonus grants (see table 8).

Table 8: Fiscal Year 2004 HOPWA Formula Funding

EMSA                 Base      Bonus   Bonus      Total HOPWA  Total HOPWA 
                     funding    funding funding  formula funding      formula 
                                           as a  when calculated funding when 
                                        percent   per cumulative   calculated 
                                        of base       AIDS casea   per living 
                                        funding                     AIDS case 
Atlanta, Ga.   $4,262,000   $637,000     15%             $264         $573 
Baltimore, Md.  3,940,000  3,996,000     101              463        1,039 
Baton Rouge,      666,000  1,147,000     172              626        1,290 
La.                                                           
Bridgeport,       752,000     27,000       4              238          476 
Conn.                                                         
Charleston,       411,000      7,000       2              234          480 
S.C.                                                          
Chicago, Ill.   5,622,000  2,716,000      48              341          805 
Columbia, S.C.    626,000    644,000     103              466          824 
Detroit, Mich.  1,624,000    355,000      22              280          749 
District of     5,626,000  6,176,000     110              482          939 
Columbia                                                      
Fort            3,337,000  2,903,000      87              430          954 
Lauderdale,                                                   
Fla.                                                          
Jackson, Miss.    449,000    275,000      61              371          728 
Jacksonville,   1,195,000    369,000      31              301          623 
Fla.                                                          
Memphis, Tenn.    920,000  1,214,000     132              533        1,000 
Miami, Fla.     6,149,000  4,566,000      74              400          934 
New Haven,        937,000    295,000      31              302          605 
Conn.                                                         
New Orleans,    1,785,000  1,207,000      68              385          887 
La.                                                           
New York, N.Y. 33,487,000 26,868,000      80              414        1,099 
Newark, N.J.    4,297,000    885,000      21              277          828 
Philadelphia,   4,340,000  3,292,000      76              404          799 
Pa.                                                           
Orlando, Fla.   1,660,000  1,529,000      92              441          913 
Wake County,      345,000      7,000       2              234          408 
N.C.                                                          
San Francisco,  6,698,000  1,864,000      28              294        1,130 
Calif.                                                        
San Juan, P.R.  4,585,000  2,555,000      56              358        1,000 
Tampa, Fla.     2,221,000    168,000       8              247          569 
West Palm       2,019,000  1,817,000      90              436          933 
Beach, Fla.                                                   
Wilmington,       566,000    232,000      41              325          624 
Del.                                                          
All other               b          0       0              230            c 
grantees                                                      

Source: GAO analysis of CDC and HUD data.

aCumulative AIDS cases are the total number of AIDS cases, both living and
dead, reported in the jurisdiction since the beginning of the epidemic in
1981.

bVaries by number of cumulative AIDS cases.

cVaries by number of living AIDS cases.

Bonus funding can be an important component of an EMSA's HOPWA formula
funding. Bonus grants exceeded base funding amounts in five EMSAs
(Baltimore, Maryland; Baton Rouge, Louisiana; Columbia, South Carolina;
Memphis, Tennessee; and the District of Columbia), and were more than 50
percent of base funding in another nine. EMSAs that did not receive bonus
funding received approximately $230 per cumulative AIDS case in fiscal
year 2004 formula funding. Because grantees other than EMSAs were not
eligible for the bonus funding, they also received $230 per cumulative
case. However, the 26 EMSAs that received bonus funding were allocated an
average of $367 per cumulative case in total formula funding, ranging from
$234 to $626 per case. If all of the formula funding had been allocated on
the basis of cumulative AIDS cases, instead of allocating base grants by
cumulative cases and bonus grants by incidence rates, each grantee would
have received $306 per case. The last column in table 8 shows that EMSAs
that received bonus funding also received more funds per living AIDS case.
59 These EMSAs received an average of approximately $816 per living case,
ranging from $408 per case in Wake County, North Carolina, to $1,290 per
case in Baton Rouge, Louisiana. Those grantees that did not receive bonus
funding received about $503 per living case, ranging from $387 to $627 per
case. (See app. IV).

The Use of Revised OMB Metropolitan Area Definitions Would Change Most EMA
Boundaries, but Increase in ELCs within EMAs Would Be Minimal

Title I EMA boundaries were made permanent by the 1996 amendments to the
CARE Act, and they have not been altered to conform to OMB's 2004
definitions of metropolitan areas. 60 Since existing Title I and Title II
organizational and administrative arrangements within states and EMAs are
connected to current EMA boundaries, changing EMA boundaries to conform to
OMB 2004 metropolitan areas could disrupt those arrangements. On the other
hand, adopting the 2004 OMB definitions for EMAs would reflect the same
metropolitan areas for which statistical agencies make data available to
the public and reflect the 2000 decennial census demographic data. OMB
recommends that policymakers review and consider the appropriateness of
the new definitions of metropolitan area boundaries for program purposes.

If OMB's 2004 definitions of metropolitan area 61 boundaries were used to
establish the area to be considered when defining an EMA under Title I, 62
the service area boundaries would change for the majority of the current
EMAs. 63 To demonstrate the changes involved in reconfiguring EMA
boundaries to conform to the new metropolitan areas, we chose a method
that could be used for this conversion. As described in appendix I, the
method we chose would combine new metropolitan areas so as to minimize
changes to current EMA boundaries. 64

If our method of converting EMA boundaries to metropolitan areas using the
2004 definitions were incorporated in the CARE Act funding formulas, the
service area boundaries of more than half of current EMAs would change. In
addition, 5 EMAs would be consolidated to 2, reducing the total number of
EMAs from 51 to 48. 65 We found that 31 of the 51 current EMAs would add,
lose, or both add and lose counties in their service areas. For example,
the Atlanta EMA would add 8 counties, the Las Vegas EMA would lose 2
counties, and the Newark EMA (New Jersey) would both add 2 counties and
lose 1 other county. Overall, 17 counties would no longer be part of an
EMA and 53 counties that were not previously included in an EMA would be
added to the service area of a newly reconfigured EMA. Service area
boundaries of 20 current EMAs would not change if the new OMB metropolitan
area definitions were adopted. (See app. VII.)

Changing the service area boundaries of current Title I EMAs to reflect
the new OMB metropolitan area definitions would result in most EMAs having
a change in the number of ELCs within their boundaries, and the total net
effect would be an increase of ELCs counted under Title I of less than 1
percent. Any ELCs that would no longer be counted under Title I would
continue to be considered for purposes of Title II base grants as ELCs
outside an EMA. Our analysis of the change in ELCs resulting from a change
in EMA boundaries to the new OMB definitions shows that 19 of the 51
current EMAs would have less than a 2 percent change in their number of
ELCs, and 23 EMAs would have no change in the number of ELCs in their
service area. In total, these 42 EMAs represent about 88 percent of the
total number of Title I ELCs. Of the remaining 9 EMAs, 3 EMAs would
experience a gain or loss of more than 9 percentage points in their ELCs.
The Dutchess County EMA (New York) would have about a 93 percentage-point
increase in ELCs (a gain of 486 in the number of ELCs) as a result of
adding Orange County to its service area. In New Jersey, Middlesex would
have a 79 percentage-point increase in ELCs (a gain of 979 in the number
of ELCs) by adding Monmouth and Ocean Counties. The Boston EMA would have
about a 9 percentage-point decrease (a loss of 554 in the number of ELCs)
because Bristol County (Massachusetts) would be reassigned from the Boston
EMA to the Providence (Rhode Island) metropolitan area, which is not an
EMA. Because the overall change in the number of Title I ELCs that would
result from EMA service area boundary changes under the new OMB
definitions would be an increase of less than 1 percent (a net gain of
1,742 in the number of ELCs), a minimal overall effect on funding per ELC
would be expected.

Funding Effect of Using HIV Case Counts Would Depend on Multiple Factors

CARE Act and HOPWA funding would have shifted among grantees if HIV case
counts had been used with a measure of persons living with AIDS to
allocate fiscal year 2004 formula grants. While all states and Puerto Rico
have established HIV case-reporting systems, IOM identified
characteristics of these systems that limit their appropriateness for the
distribution of CARE Act and HOPWA funds. 66 We found that up to 13
percent of CARE Act funding would have shifted if HIV case counts had been
used with ELCs in the distribution of fiscal year 2004 funds and if the
hold-harmless and minimum-grant provisions we considered were maintained.
67 Larger changes for individual grantees would have occurred with some
grantees more than doubling their funding. Grantees in the South and
Midwest would generally have received more funding from using HIV cases in
funding formulas. 68 However, there would have been grantees that would
have received increased funding and grantees that would have received
decreased funding in every region of the country. Larger funding shifts
would have occurred without these CARE Act hold-harmless and minimum-grant
provisions. HOPWA funding would also have shifted if HIV cases along with
living AIDS cases had been used to determine funding rather than
cumulative AIDS case counts. Differences in HIV case-reporting systems
would affect funding allocations, and we found that funding would have
tended to shift to jurisdictions with older HIV-reporting systems.
Jurisdictions with older HIV-reporting systems tend to have more reported
HIV cases compared with their number of AIDS cases than do jurisdictions
with newer reporting systems.

Current HIV Case-reporting Systems Have Limitations for Providing Case
Counts for Funding Allocations

In order to monitor HIV infection, the states and Puerto Rico have
established HIV case-reporting systems under which individuals who have
been diagnosed with HIV are reported to health departments by physicians
and other practitioners. 69 In 2000 we reported that HIV cases accounted
for a much smaller percent of total HIV/AIDS cases in states with newer
HIV-reporting systems. 70 In its 2004 report, IOM updated our earlier
analysis and identified several limitations in the ability of these
jurisdictions to provide accurate HIV case counts to CDC for use in CARE
Act funding allocations. Among these limitations, IOM found that the
maturity of HIV case-reporting systems continued to vary widely across
grantees. The earliest HIV-reporting systems were established in Colorado,
Minnesota, and Wisconsin in 1985, followed by most southern and other
midwestern states prior to 1995. The newest systems were established after
2003 in six states and Philadelphia, Pennsylvania. 71 Case-reporting
systems need several years to become fully operational. Practitioners need
to be made aware of the requirement to report new HIV cases and the
methods for doing so. Existing cases also need to be reported by
practitioners and entered into the system. Grantees with newer systems may
not have collected and entered data on existing cases, and, consequently,
may underreport the number of HIV cases. Underreporting of HIV cases in
states with newer HIV-reporting systems would result in grantees receiving
less funding than they would be entitled to receive according to the
actual number of HIV/AIDS cases.

IOM also found that differences in how jurisdictions report HIV case
counts to CDC preclude HRSA's use of those case counts in the distribution
of CARE Act funds. 72 While some HIV case-reporting systems are
code-based, CDC will only accept name-based case counts as no code-based
system has met its quality criteria as of January 2006. 73 Therefore, HIV
cases reported using codes rather than names would not be counted in
distributing CARE Act funds, if HIV case counts were used in funding
formulas. As of December 2005, thirteen states have some form of a
code-based system rather than a name-based system. 74 CDC does not accept
the code-based data principally because methods have not been developed to
make certain that a code-reported HIV case is only being counted once
across all reporting jurisdictions. 75 Table 9 shows the 39 jurisdictions
where HIV case counts are accepted by CDC and the 13 jurisdictions where
they are not accepted, and the year in which each jurisdiction established
its HIV-reporting system.

Table 9: CDC Acceptance of HIV Case Counts and Year of Establishment of
HIV-reporting Systems, December 2005

Accepted              Not accepted                
Colorado (1985)       Maryland (1994)             
Minnesota (1985)      Massachusetts (1999)        
Wisconsin (1985)      Illinois (1999)d            
Idaho (1986)          Maine (1999)e               
South Carolina (1986) Washington (1999)           
Arizona (1987)        Montana (2000)              
Missouri (1987)       Rhode Island (2000)         
Alabama (1988)        Vermont (2000)              
Indiana (1988)        Delaware (2001)             
Mississippi (1988)    District of Columbia (2001) 
North Dakota (1988)   Hawaii (2001)               
Oklahoma (1988)       Oregon (2001)               
South Dakota (1988)   California (2002)           
Arkansas (1989)       
Utah (1989)           
Virginia (1989)       
West Virginia (1989)  
Wyoming (1989)        
North Carolina (1990) 
Ohio (1990)           
Michigan (1992)       
Nevada (1992)         
New Jersey (1992)     
Tennessee (1992)      
Louisiana (1993)      
Nebraska (1995)       
Florida (1997)        
Iowa (1998)           
New Mexico (1998)     
Alaska (1999)         
Kansas (1999)         
Texas (1999)          
New York (2000)       
Pennsylvania (2002)a  
Georgia (2003)        
Puerto Rico (2003)    
Kentucky (2004)       
Connecticut (2005)b   
New Hampshire (2005)c 

Sources: CDC, IOM, Connecticut, Kentucky, and Philadelphia. Connecticut,
Kentucky, and Philadelphia provided us with updated information about
their HIV case-reporting systems.

Notes: Currently, CDC will only accept name-based case counts.

aName-based HIV reporting has been established in all parts of
Pennsylvania except Philadelphia since 2002. Philadelphia was given
permission by the state to establish code-based HIV reporting, and the
system began in 2004. However, in August 2005, the Philadelphia Board of
Health voted to implement a name-based HIV-reporting system. This system
went into effect in October 2005. Philadelphia is in the process of having
its HIV surveillance data certified by CDC; once certified, its data will
be accepted by CDC.

bConnecticut established mandatory name-based HIV reporting in 2005.
Previously, name-based reporting was only required for pediatric cases.

cNew Hampshire established mandatory name-based HIV reporting in 2005.
Previously, HIV cases could be reported using the patient name, a code, or
no identifier at all.

dIllinois established name-based HIV reporting in January 2006. It is in
the process of having its HIV surveillance data certified by CDC and, once
certified, its data will be accepted by CDC.

eMaine established name-based HIV reporting in January 2006. It is in the
process of having its HIV surveillance data certified by CDC and, once
certified, its data will be accepted by CDC.

The Use of HIV Case Counts in Funding Formulas Would Have Changed the
Distribution of Fiscal Year 2004 CARE Act and HOPWA Funds

While we are aware of differences in the HIV data across jurisdictions, we
conducted this analysis in light of the CARE Act requirement that HIV case
counts be used for the distribution of Title I and Title II formula grants
not later than fiscal year 2007. We used two approaches to examine the
potential effect of including HIV cases in addition to persons living with
AIDS in fiscal year 2004 CARE Act and HOPWA funding formulas. We found
that some CARE Act fiscal year 2004 funding would have shifted among
grantees if HIV case counts and ELCs had been used to allocate the funds.
While our analyses indicate that up to 13 percent of CARE Act funding
would have shifted, larger changes for individual grantees would have
occurred. Southern and midwestern grantees would generally have received
more funding, but there would have been grantees that would have received
increased funding and grantees that would have received decreased funding
in every region of the country. Funding changes in our model would have
been larger without the hold-harmless and minimum-grant provisions that we
included. There would also have been at most a 15 percent shift in HOPWA
funding if HIV cases were used to allocate funding, although there would
have been larger changes for some grantees. 76 CARE Act and HOPWA funding
changes could have resulted from the number of people living with HIV/AIDS
in each jurisdiction or differences in HIV case-reporting systems.

Methodological Approaches Used

We used two approaches to examine the effect of using HIV cases in
addition to AIDS cases 77 in funding formulas for CARE Act Title I and
Title II base grants, ADAP base grants, and HOPWA base funding in the
states and Puerto Rico. Under the first approach, we used HIV and AIDS
case counts for the 35 grantees from which CDC accepted HIV data. 78
Because CDC did not receive HIV case counts from the other 17 grantees, we
used only the AIDS case counts received by CDC for these grantees.
Consequently, for some grantees we used HIV and AIDS case counts, but for
others we used only AIDS case counts. This approach reflects the data that
would have been used if funding allocations were based on the HIV and AIDS
case counts received by CDC in time for determining fiscal year 2004
formula grants. Under the second approach, we used the same HIV and AIDS
case counts as our first approach, but supplemented these data with the
code-based HIV case counts collected by the grantees from which CDC did
not receive HIV data. 79 We obtained these HIV case counts directly from
these jurisdictions. 80

For both approaches, we calculated the grantee's percentage of the total
number of HIV/AIDS cases in each jurisdiction 81 and estimated the fiscal
year 2004 formula grants that each would have received. Under each
approach, CARE Act formula grants were calculated both with certain
hold-harmless and minimum-grant provisions and again without those
provisions. 82 Eliminating hold-harmless and minimum-grant provisions was
done to reveal the full effect of distributing fiscal year 2004 funding
solely according to HIV/AIDS data available at that time. We also
estimated the effect of using HIV cases and living AIDS cases for HOPWA
base funding. Although there are limitations associated with the
underlying data, the results of our analyses indicate the general effect
of using HIV and AIDS cases to distribute CARE Act and HOPWA formula
funding. (See app. I for a discussion of the limitations in the data.)

Changes in CARE Act Funding Using HIV Cases and Hold-harmless and
Minimum-grant Provisions

Our analyses indicate that for fiscal year 2004 as much as 13 percent of
Title I, Title II, and ADAP base grants would have shifted, with southern
and midwestern grantees being the primary beneficiaries, if hold-harmless
and minimum-grant provisions were maintained. However, there would have
been grantees that would have received increased funding and grantees that
would have received decreased funding in every region of the country.
Changes in funding could have resulted from the actual number of HIV/AIDS
cases living in each jurisdiction or from differences across jurisdictions
in HIV case-reporting systems. The funding changes under each of our
approaches would have been larger if we had not applied the hold-harmless
and minimum-grant provisions.

Title I Base Funding

Title I base grant funding would have shifted among grantees under both
our approaches, but because the funds necessary to meet the hold-harmless
provision are taken from funds that would otherwise be used for
supplemental grants, the overall effect on Title I EMAs is unclear. 83 The
Title I base grant includes (1) funding amounts determined by the number
of ELCs and (2) the hold-harmless amounts, if applicable. In fiscal year
2004, a total of about $8.0 million was needed to fund the hold-harmless
payments for EMAs. The amount of Title I hold-harmless funding for all
EMAs would have increased from $8.0 million to $43.3 million under our
first approach in which we used only HIV data received by CDC and ELCs. It
would have increased to $29.4 million under our second approach in which
we used the HIV case counts collected by CDC, the code-based HIV counts we
collected from the grantees, and ELCs. In order to meet the hold-harmless
levels, funds would have to be deducted from the amounts otherwise
available for Title I supplemental grants. Supplemental grants are divided
among all EMAs using a competitive application process based on the
demonstration of severe need and other criteria. Because these awards are
made competitively, it is unclear how the reduction in funding for
supplemental grants would have affected individual EMAs and, therefore,
what the overall effect on funding for each EMA would have been under our
two approaches.

Under the first approach-using ELCs and HIV cases when accepted by CDC and
only ELCs elsewhere-13 EMAs would have received a total of $2.8 million
less in fiscal year 2004 Title I base grants, about 1 percent of the total
Title I base grants. Twenty-nine grantees would have received $38.1
million in additional Title I base grant funding, about 13 percent of
total Title I base grants, if HIV cases and ELCs had been used to allocate
funding instead of just ELCs. The other 9 EMAs would have had no change in
their funding. The effect on certain EMAs would have been large, with the
Denver EMA more than doubling its Title I base funding and 16 others
receiving at least a 25 percent increase in funding. Of the 29 that would
have received more funding, 13 are in the South. In addition, 5 of the 6
EMAs in the Midwest and 8 of 12 EMAs in the Northeast would have received
increased funding. However, only 3 of 14 EMAs in the West would have
received increased funding. 84

Under the second approach-using the HIV case counts collected by CDC, the
code-based HIV counts we collected from the grantees, and ELCs- 15 EMAs
would have received a total of $1.9 million less in fiscal year 2004 Title
I base grants, about 1 percent of the total Title I base grants.
Twenty-eight grantees would have received $23.3 million more in fiscal
year 2004 Title I base grants, about 8 percent of total Title I base
grants. Eight EMAs would have had no change in their funding. Some EMAs
would have received large increases in funding, with the Denver EMA more
than doubling its Title I base grant funding and 9 others receiving at
least a 25 percent increase in funding. Of the 28 EMAs that would have
received additional funding, 10 are in the South. All 6 midwestern EMAs
would have received additional funding. Seven of 12 EMAs in the Northeast
and 5 of 14 EMAs in the West would have received increased funding.
Appendix VIII shows the results of the analyses for each EMA under each
approach.

Title II Base Funding

There would be some shifting of funds if HIV cases and ELCs had been used
to allocate CARE Act Title II base grants while maintaining the
hold-harmless and minimum-grant provisions. 85 Most southern and
midwestern grantees would receive increased funding under either approach
we used for analysis. Under the first approach-using ELCs and HIV cases
when accepted by CDC and only ELCs elsewhere-about 5 percent or $14.3
million of Title II base grants would have shifted among grantees. Unlike
funding for the Title I hold-harmless provision, the amounts necessary to
fund the Title II base grant hold-harmless and minimum-grant provisions
are subtracted from the base grants of those states that did not qualify
for funding under these provisions. Consequently, the total amount of
funding increases received by some Title II grantees would have to be
equal to the total decreases received by other grantees. Twenty-one
grantees would have received additional funding in their Title II base
grants, and 22 would have received less. Nine grantees would have had no
change in their funding. Of the 21 that would have received more funding,
9 are in the South and 7 in the Midwest. Of the 22 that would have
received less funding, 6 are in the Northeast and 5 are in the West.
Changes in funding for individual grantees would have ranged from a 150
percent increase in North Dakota and Wyoming to a 22 percent decrease in
Delaware and the District of Columbia.

The second approach-using the HIV case counts accepted by CDC, the
code-based HIV counts we collected from the grantees, and ELCs-would yield
a smaller shift in funding. Under this approach, approximately 4 percent
or $12.6 million of fiscal year 2004 Title II base grants would have
shifted. Of the 22 grantees that would have received additional funding,
10 are in the South and 7 in the Midwest. Among those that would have
received less funding, 4 are in the Northeast and 4 are in the West.
Twenty grantees would have received less funding and 10 would have
received the same amount. Funding changes for individual grantees would
have ranged from a 150 percent increase in North Dakota and Wyoming to a
22 percent decrease in Delaware and the District of Columbia. Appendix IX
shows the results of these analyses for each grantee under each approach.

While a majority of southern grantees would have received increased
funding under both approaches, the amount of the increase would have been
relatively small. Southern grantees would have received a total of about
$430,000 more funding under our first approach and about $640,000 under
the second approach. This relatively small shift can be attributed to the
fact that southern states generally would not benefit from the
minimum-grant and hold-harmless provisions. For example, many southern
states would have their grants reduced in order to fund the hold-harmless
provision. Midwestern grantees would have received larger dollar and
percent increases in funding than the southern grantees under both
approaches.

ADAP Base Funding

Our analyses indicate that there would have been some shifting of funding
for ADAP base grants if HIV and AIDS case counts had been used to
determine allocations while maintaining the hold-harmless provision, 86
with southern and midwestern grantees generally being among the areas that
would have received increased funding. 87 Under the first approach-using
ELCs and HIV cases when accepted by CDC and only ELCs elsewhere-about 12
percent or $85.2 million of fiscal year 2004 ADAP base grants would have
shifted among grantees. The amounts necessary to fund the ADAP base grant
hold-harmless provision are subtracted from the ADAP base grants of those
states that did not qualify for hold-harmless funding. Consequently, the
total amount of funding increases received by some Title II grantees must
be equal to the total decreases received by other grantees. Thirty-one of
the 52 grantees would have received additional funding in their ADAP base
grants if HIV cases and ELCs had been used to allocate funding instead of
just ELCs. Of the 31 that would have received more funding, 12 are in the
South and 11 in the Midwest. The funding changes for some grantees would
have been large. For example, Colorado's allocation would have doubled and
South Dakota's would have increased by 84 percent while funding would be
reduced by 38 percent in Delaware, the District of Columbia, Illinois,
Kentucky, and Maryland.

The second approach-using the HIV case counts accepted by CDC, the
code-based HIV counts we collected from the grantees, and ELCs-yields a
smaller shift in funding. Under this approach, approximately 9 percent or
$65.2 million of fiscal year 2004 ADAP base grants would have shifted. Of
the 35 grantees that would have received additional funding, 12 are in the
South and 10 are in the Midwest. Funding changes for some grantees would
have been large. For example, the allocation for Montana would have
increased 93 percent and the allocation for Colorado 84 percent, while
funding would have declined by 40 percent in the District of Columbia and
by 38 percent in Kentucky. Appendix X shows the results of these analyses
for each grantee under both approaches.

Changes in CARE Act Formula Funding Would Be Larger If Hold-harmless and
Minimum-grant Provisions Were Not in Effect

Hold-harmless provisions limit how much funding can decline from one grant
period to the next. However, while these provisions limit changes in
funding they also reduce a program's ability to respond to changing need.
Minimum-grant provisions guarantee that no grantee will receive less than
a specified funding amount. These provisions also limit how funding can be
distributed. 88

Changes in CARE Act funding levels for Title I base grants, Title II base
grants, and ADAP base grants caused by shifting to HIV cases and AIDS
cases would be larger-up to 24 percent-if the current hold-harmless or
minimum-grant amounts were not in effect than if they were in effect. 89
Consider the hypothetical situation in which an EMA or Title II grantee
received a $2 million base grant award according to its number of ELCs.
Assume that in the following year, the formula is changed so that HIV
cases and ELCs are used to determine funding allocations, and the grantee
is then only entitled to $1 million. However, there is a hold-harmless
provision that guarantees the grantee 98 percent of what it received the
previous year. The grantee would receive 98 percent of its $2 million
allocation, or $1.96 million, largely offsetting the reduction in funding
due to the shift to HIV cases and ELCs. The change in funding with the
hold-harmless provision would be a decrease of $40,000, but the loss would
grow to $1,000,000 without the hold-harmless provision. If a grantee
qualified for $100,000 in formula funding using HIV case counts and ELCs,
but the minimum award was $500,000, the grantee would receive $500,000
because of the minimum-grant provision, thereby offsetting the changes due
to using HIV cases and ELCs.

Title I Base Funding

Under both our methodological approaches, Title I funding would have been
affected by eliminating the Title I base grant hold-harmless provision. 90
If the hold-harmless provision had been eliminated, the number of EMAs
that would have received less Title I base grant funding would have
increased from 13 to 23 under our first approach-using ELCs and HIV cases
when accepted by CDC and only ELCs elsewhere-and from 15 to 24 under our
second approach-using the HIV case counts collected by CDC, the code-based
HIV counts we collected from the grantees, and ELCs. 91 The effect of the
hold-harmless provision on an individual grantee can be illustrated with
the New Haven EMA. New Haven, which would have had no change in base grant
funding if the hold-harmless provision was maintained would have had Title
I base grant funding reductions of 31 and 35 percent under the first and
second approaches, respectively, without the hold-harmless provision.
Overall, southern and midwestern EMAs would gain funding under both
approaches whether or not the hold-harmless provision was maintained while
northeastern EMAs would lose funding only under our second approach and
only if the hold-harmless provision was not maintained. 92 However, in all
four regions of the country, there would have been EMAs that would have
received increased funding and EMAs that would have received decreased
funding. Appendix XI shows the results of our analyses for Title I base
grants if the hold-harmless provision was not maintained.

Title II Base Funding

The hold-harmless and minimum-grant provisions have a large effect on
funding shifts in Title II base grants. Under our first approach-using
ELCs and HIV cases when accepted by CDC and only ELCs elsewhere- 14
percent of Title II base grants would have shifted among grantees if the
hold-harmless and minimum-grant provisions had been eliminated, while 5
percent would have shifted if they had been maintained. Under our second
approach-using the HIV case counts collected by CDC, the code-based HIV
counts we collected from the grantees, and ELCs-10 percent would have
shifted if the provisions were eliminated and 4 percent if they had been
maintained. The importance of these provisions can be illustrated by
examining individual grantees. For example, Vermont, which received a
minimum grant of $500,000 in fiscal year 2004, would have had a decrease
of 74 percent under approach one and 52 percent under approach two if the
hold-harmless and minimum-grant provisions had not been maintained.
However, it would have had no change in funding if these provisions had
been maintained. California would have received decreases of $11.8 million
under our first approach and $5.0 million under our second approach if the
provisions had been eliminated, but the state would have had no change in
funding if the provisions had been maintained. Conversely, North Carolina
would have received $5.0 million in additional funding under our first
approach and $4.0 million under our second approach if the hold-harmless
and minimum-grant provisions had not been maintained. It would have
received $2.4 million and $2.1 million additional under each approach
respectively if the provision had been maintained. Southern and midwestern
grantees would gain funding under both approaches whether or not the
hold-harmless and minimum-grant provisions had been maintained, while
northeastern grantees would lose funding. 93 However, in all four regions
of the country, there would have been grantees that would have received
increased funding and grantees that would have received decreased funding.
Appendix XII shows the results of our analyses for Title II base grants if
the hold-harmless and minimum-grant provisions were not maintained.

ADAP Base Funding

The overall effect of the hold-harmless provision is smaller on funding
shifts for the ADAP base grants. 94 Under our first approach-using ELCs
and HIV cases when accepted by CDC and only ELCs elsewhere- 14 percent
instead of 12 percent of ADAP base funding would have shifted among
grantees if the hold-harmless provision was eliminated. Ten percent
instead of 9 percent of the funding would have shifted under our second
approach-using the HIV case counts collected by CDC, the code-based HIV
counts we collected from the grantees, and ELCs. The reason for the
smaller effect on the ADAP base grants than on the Title I and Title II
base grants is the increase in ADAP base funding since fiscal year 2000.
In fiscal year 2000, $528 million was distributed to grantees while $728
million was distributed in fiscal year 2004. Because of these increases,
the hold-harmless provision had less effect in our analyses. However,
under all our scenarios grantees in the Northeast and West would have
received less total funding while grantees in the Midwest and South would
have received more. In all four regions of the country, there would have
been grantees that would have received increased funding and grantees that
would have received decreased funding. For example, in the Northeast, New
Jersey would have gained funding and New York would have lost funding
under both our approaches. In the South, Alabama would gain funding and
Georgia would lose funding under both our approaches. Appendix XIII shows
the results of our analyses for ADAP base grants if the hold-harmless
provision had not been in effect.

HOPWA Base Funding Would Generally Shift If HIV Cases Were Used in Formula
Allocations

There would have been some shifting of funds if HIV and living AIDS case
counts 95 had been used to allocate HOPWA base grants instead of
cumulative AIDS cases under either of our methodological approaches-with
or without the code-based HIV case counts-with southern and midwestern
grantees generally being among the jurisdictions that would have received
increased funding. 96 Under the first approach-using living AIDS cases and
HIV cases when accepted by CDC and only living AIDS cases elsewhere-about
15 percent or $30.0 million of fiscal year 2004 HOPWA base grants would
have shifted among grantees. Seventy of 117 grantees would have received
additional funding in their HOPWA base grants if living HIV and AIDS cases
had been used to allocate funding. Six grantees would have more than
doubled their funding. 97 Thirty-five of 47 southern grantees 98 and 18 of
the 20 midwestern grantees would have received more funding. Southern
grantees would have received an additional $15.8 million (22 percent) in
funding while those in the Midwest would have received an additional $3.3
million (17 percent). Seventeen of the 24 northeastern grantees and 14 of
the 24 western grantees would have received less funding. The northeastern
and western grantees would have received $6.3 million (10 percent) and
$9.7 million (24 percent) less in funding respectively.

The second approach-using the HIV case counts accepted by CDC, the
code-based HIV counts we collected from the grantees, and living AIDS
cases-yields an overall smaller shift in funding although changes would
have been larger in the Midwest and Northeast. Under this approach,
approximately 13 percent or $25.6 million of fiscal year 2004 HOPWA base
grants would have shifted, with Maryland and Charlotte, North Carolina,
more than doubling their funding. Of the 82 grantees that would have
received additional funding, 39 are in the South, 19 in the Midwest, 14 in
the West, and 10 in the Northeast. Overall, the South would have received
$13.7 million (19 percent) in additional funding and the Midwest would
have received an additional $4.0 million (21 percent). The Northeast would
have received $8.5 million (14 percent) less in funding and the West $5.8
million (15 percent) less. Appendix XIV shows the results of these
analyses for each jurisdiction under both approaches.

Differences in Case-reporting Systems Would Affect Allocations

One explanation for the changes in funding allocations when HIV cases and
either ELCs or living AIDS cases are used-whether or not the code-based
HIV case counts are included-instead of only AIDS cases 99 is the maturity
of HIV case-reporting systems. We found that those grantees that would
receive increased funding from the use of HIV cases tend to be those with
the oldest HIV case-reporting systems. Those grantees with the oldest
reporting systems include 11 southern and 8 midwestern states whose
HIV-reporting systems were implemented prior to 1995. As shown in table
10, jurisdictions with long histories of counting HIV cases tend to have
many more reported HIV cases compared with their number of ELCs than do
jurisdictions with less-mature reporting systems. This difference is
likely because jurisdictions with newer systems do not have reports on
many cases of HIV that were diagnosed before their reporting systems were
established. 100 This divergence can be illustrated by comparing Wisconsin
and Delaware, two states with similar numbers of AIDS cases. Wisconsin
began reporting HIV cases in 1985 while Delaware began in 2001. In
Wisconsin, as of June 2003, there were about 50 percent more reported HIV
cases than AIDS cases, or 2,287 HIV cases and 1,507 AIDS cases. As of June
2003, the 909 reported HIV cases in Delaware were about 40 percent less
than the 1,518 ELCs. This variability could be reduced as Delaware
identifies more preexisting HIV cases. However, the variability between
HIV cases and ELCs would remain if there was a difference in the actual
number of HIV cases.

Table 10: Reported HIV Cases and ELCs as of June 2003

HIV case-reporting system      Number of jurisdictionsa Ratio of HIV cases 
start date                                                         to ELCs 
1985-1991                                            21               1.42 
1992-1998                                            11               1.01 
1999-2002                                            17               0.68 

Source: GAO analysis of CDC, HRSA, and state data.

aGeorgia, Kentucky, and Puerto Rico are not included in this table because
they established their HIV-reporting systems after 2002. Connecticut and
New Hampshire established their name-based HIV-reporting system in 2005.
However, in this table, Connecticut is classified as having established
its reporting system in 2001 (and so is included in the 1999-2002 time
period) since state officials provided us HIV case counts based on the
system in operation as of June 2003. New Hampshire is classified as having
established its reporting system in 1990 (and so is included in the
1985-1991 time period), because state officials provided us HIV case
counts based on the system in operation as of June 2003.

Under either approach, grantees might receive increased funding because
other grantees did not yet have an accurate measure of HIV case counts.
IOM has reported that it could take from 18 months to several years after
the implementation of an HIV-reporting system before there would be valid
estimates of the number of people living with HIV. 101

The maturity of the HIV-reporting systems can be linked to whether a
jurisdiction has a name- or code-based system. As discussed earlier, CDC
does not currently accept HIV case reports from code-based systems.
However, even if code-based data were incorporated into the CDC case
counts, the age of the code-based systems could still be a factor since
the code-based systems tend to be newer than the name-based systems. As of
December 2005, twelve of the 13 code-based systems were implemented in
1999 or later, compared with 10 of the 39 name-based systems. The effect
of the maturity of the code-based systems could be increased if, as CDC
believes, name-based systems can be executed with more complete coverage
of cases in much less time than code-based systems. As a result,
jurisdictions with code-based systems could find themselves with
undercounts of HIV cases for longer periods of time than jurisdictions
with name-based systems.

The use of HIV cases in CARE Act funding formulas could result in
fluctuations in funding over time because of newly identified preexisting
HIV cases. Grantees with more mature HIV-reporting systems have generally
identified more of their HIV cases. Therefore, if HIV cases were used to
distribute funding, these grantees would tend to receive more funds. As
grantees with newer systems identify and report a higher percentage of
their HIV cases, their proportion of the total number of ELCs and HIV
cases in the country would increase and funding that had shifted away from
states with newer HIV-reporting systems would shift back, creating
potentially significant additional shifts in program funding. Without
corresponding increases in CARE Act funding, this increase in identified
HIV cases could cause grantees with more mature systems to experience
funding decreases. Hold-harmless provisions would protect grantees with
older reporting systems from funding losses. However, grantees with newer
systems could receive less funding per case because funds would be needed
to cover hold-harmless provisions.

Conclusions

The funding provided under the CARE Act and HOPWA has filled important
gaps in communities throughout the country, but as Congress reviews these
programs, it is important to understand how much funding can vary across
communities with comparable numbers of persons living with AIDS. While
provisions in the formulas have served specific purposes, such as
maintaining consistent funding from year to year, it is clear that the
level of funding available per AIDS case is quite variable because of
these provisions:

           o  The use of ELCs-AIDS cases reported over the past 10 years
           weighted by survival rates-and the use of 2- and 5-year cumulative
           reported AIDS cases for CARE Act funding results in AIDS case
           counts that do not reflect the number of persons who could be
           served by the program because many persons with AIDS live longer
           than 10 years after their disease is reported, deceased cases are
           included in the case counts, and cases diagnosed prior to the
           reporting period are not included.
           o  Considerably more CARE Act funding has gone to some grantees
           than others even though they have similar numbers of cases because
           of the counting of ELCs in EMAs for both Title I base funding and
           Title II base funding, hold-harmless provisions that protect Title
           I, Title II, and ADAP base grant funding levels, the
           grandfathering of EMAs so that metropolitan areas designated as
           EMAs for fiscal year 1996 continue to be eligible for Title I
           funding, and the division of Emerging Communities into two tiers
           with equal funding of each tier without regard to the number of
           communities or the number of reported AIDS cases in each tier.
           o  The use of cumulative AIDS cases to determine eligibility for
           HOPWA formula grants, including for bonus grants, and the amount
           of HOPWA base grants has led to disproportionate funding per
           living AIDS case because the formula counts deceased cases in
           addition to living cases, thereby resulting in increased funding
           for areas with early outbreaks.

           The CARE Act Title II hold-harmless provision that is funded from
           amounts that would otherwise be available for ADAP Severe Need
           grants has had little effect so far as the amounts needed to fund
           this provision have been comparatively small. However, reducing
           funds to be made available for qualifying states could adversely
           affect the states with severe need in the future if the amounts
           needed to fund the hold-harmless provision increase.

           Congress recognized in the 2000 CARE Act amendments that the CARE
           Act benefits many people whose HIV infection has not progressed to
           AIDS when it required that HIV case counts be used in the
           distribution of funds. The inclusion of HIV cases in the CARE Act
           funding formulas by fiscal year 2007 could eventually improve the
           targeting of funding to needy individuals with HIV disease.
           However, it could result in significant shifts in program funding
           that may not be related to the geographic distribution of HIV/AIDS
           cases because of differences in the type and maturity of the
           reporting system used in each state.

Matters for Congressional Consideration

While only AIDS case counts are currently used for determining CARE Act
formula funding, Congress has required that HIV case counts be
incorporated into the funding formulas not later than fiscal year 2007.
Regardless of when HIV case counts are incorporated, issues will still
exist regarding how AIDS cases are used in the formulas and the effect
various provisions have on funding. If Congress wishes CARE Act funding to
more closely reflect the distribution of persons living with AIDS, and to
more closely reflect the distribution of persons living with HIV/AIDS when
HIV cases are incorporated into the funding formulas, it should take the
following five actions:

           o  revising the funding formulas used to determine grantee
           eligibility and grant amounts using a measure of living AIDS cases
           that does not include deceased cases and reflects the longer lives
           of persons living with AIDS,
           o  eliminating the counting of cases in EMAs for Title I base
           grants and again for Title II base grants,
           o  modifying the hold-harmless provisions for Title I, Title II,
           and ADAP base grants to reduce the extent to which they prevent
           funding from shifting to areas where the epidemic has been
           increasing,
           o  modifying the Title I grandfather clause, which protects the
           eligibility of metropolitan areas that no longer meet the
           eligibility criteria, and
           o  eliminating the two-tiered structure of the Emerging
           Communities program.

           If Congress wishes to preserve funding for the ADAP Severe Need
           grants, it should revise the Title II hold-harmless provision that
           is funded with amounts set aside for ADAP Severe Need Grants.

           If Congress wishes HOPWA funding to more closely reflect the
           distribution of persons living with AIDS, it should change the
           program so that HOPWA formula grant eligibility, including for
           bonus grants, and base grant funding allocations are based on a
           measure of living AIDS cases.

Agency Comments and Our Evaluation

HHS and HUD provided written comments on a draft of this report. HHS and
HUD generally agreed with our identification of issues in the funding
formulas. Their comments are reprinted in appendixes XV and XVI. HHS
commended us for its comprehensive approach and ambitious analysis that
pulled together data from many disparate sources. HUD noted that it
appreciated that the report seeks to improve the targeting of federal
resources to better assist those with HIV/AIDS.

HHS noted that we identified various deficiencies in the current HIV data.
However, HHS suggested that we did not examine the distribution
differences that would result from incorporating HIV cases into the CARE
Act funding formulas. HHS noted that we did not assess the potential
usefulness of HIV data in funding formulas if all jurisdictions
participated in the national reporting system coordinated by CDC using
standardized methods of reporting. Such a determination was beyond the
scope of our work. However, as noted in the draft report, we present
analyses showing the impact of using HIV cases on fiscal year 2004 funding
for Title I, Title II, and ADAP base grants, which comprise the bulk of
CARE Act funding.

While HHS generally agreed with our matters for congressional
consideration, HHS made several comments on the issues these matters
address. HHS noted that our matters for congressional consideration focus
only on potential changes to the use of AIDS cases in formulas but not to
the use of HIV cases. The matters for consideration are based on current
funding formula provisions that require the use of AIDS cases. Our
discussion should not be interpreted as endorsing the superiority of using
living AIDS cases instead of HIV/AIDS cases.

Regardless of whether HIV case counts are used, the funding formula
provisions we identified will continue to affect proportional funding per
case if they are maintained. We believe that the use of AIDS case counts
that include deceased cases and do not reflect the current life spans of
persons living with AIDS will continue to be of concern. Also, various
provisions, such as allocating funding for Emerging Communities by tier
and hold-harmless provisions, will affect the distribution of funding
regardless of whether HIV cases are used in the formulas.

HHS pointed out that our assessment of the impact of hold-harmless
provisions on CARE Act formula funding appears accurate. HHS noted
disparities in funding per AIDS case that can result from counting cases
in EMAs once for Title I funding, and once again for Title II funding. HHS
also agreed with our analysis of the Emerging Communities provision; we
deleted our reference to a population threshold as an eligibility
requirement for Emerging Communities in response to its comment on this
issue. HHS concurred with our suggestion that the Title II hold-harmless
provision should be revised to preserve funding for ADAP Severe Need
grants.

HHS raised concerns that our discussion of the Title I grandfather clause
in the CARE Act could be interpreted as suggesting EMAs that continue to
receive grants because of this provision need not be funded. HHS noted
that a cessation of funding could lead to a decline in these areas'
systems of care and, by extension, a decline in the progress made in
fighting the epidemic. However, we note that these areas could receive
funding through their respective states or territories, which receive
funds under Title II. In addition, much of the improvement in care for
those with HIV/AIDS is due to the improvement in drugs, which, as
indicated in Appendix III, are primarily provided through Title II ADAP
grants. HHS noted that without Title II minimum grant amounts for states
and territories, the number of reported AIDS cases in low prevalence areas
would not be sufficient to sustain state-of-the-art HIV/AIDS care and
treatment services.

HHS also noted that we do not have a specific matter for congressional
consideration regarding the use of OMB's revised definitions of
metropolitan boundaries for determining Title I EMAs. HHS stated that the
report suggests that the revised definitions be accepted for determining
such boundaries. In the report, we discuss the methods used in our
analysis and the results of this analysis, but take no position on whether
the new definitions should be used in determining the EMA boundaries.

HHS commented that the draft report lacked specificity regarding the
process by which CDC receives HIV case counts from the states. We have
modified our report to include a discussion of this process. HHS also
stated in its comments that it would not be appropriate to use the
code-based case counts in monitoring HIV/AIDS nationally. An assessment of
whether code-based data should be used for monitoring HIV/AIDS is beyond
the scope of our work. Our purpose was to provide Congress with an
indication of the impact of using HIV cases in the CARE Act and HOPWA
funding formulas in light of the statutory requirement that HIV cases be
used in CARE Act funding formulas not later than fiscal year 2007. We have
added text to the report discussing HHS's concerns about code-based data.

HUD concurred with our matter for congressional consideration that
cumulative AIDS cases no longer be used in the HOPWA formula. HUD pointed
out that incorporation of a more current estimate of persons living with
HIV/AIDS would be more effective in targeting these HOPWA funds to
grantees. HUD stated in its comments that we did not take into account
differing housing costs across jurisdictions in the draft report. In
response to this comment, we revised the report to note that housing costs
are not currently part of the HOPWA funding formula, and consideration of
housing costs was not within the scope of our work. However, we have
clarified the draft report to note that if housing costs were included in
the funding formulas, they could justify deviations from proportional
funding per case.

HUD suggested that we not use the terms base grant and bonus grant. We
have added a note to our report to reflect that our terminology differs
from HUD's, but retained the use of bonus and base grants in order to
differentiate between the two formula funding components.

HUD expressed concern that the full effect of incorporating HIV case
counts may not be apparent by only stating the amount of funding that
would shift among grantees. We have added text to note that the changes
could result in some grantees more than doubling their funding. HUD
suggested that these analyses could be done based solely on data from
jurisdictions with CDC-accepted HIV case counts, or those jurisdictions
with mature HIV-reporting systems. However, as noted in the draft report,
we present analyses showing the impact of using only CDC-accepted HIV data
on fiscal year 2004 HOPWA base grants. We do not include an analysis using
only jurisdictions with mature HIV-reporting systems because it would
exclude many jurisdictions and we determined that such an analysis would
not be appropriate. HUD also pointed out that the draft report did not
describe the incremental effect on HOPWA allocations of using HIV cases
with living AIDS cases rather than living AIDS cases only. The draft
report provided information on this in appendix V, and we have added text
to the report to refer the reader to this appendix. HUD suggested that we
expand a footnote to further describe our analysis of HIV cases in funding
formulas. However, this information is already presented in detail in
appendix I and is also described in the text of the report.

In its comments HUD noted bonus funding can provide a significant amount
of resources to those eligible and that this funding can have a large
effect on formula funding per AIDS case. As noted in the draft report, we
show the amount of base funding and bonus funding that each grantee
received in fiscal year 2004 and state that funding differences per case
are due in part to the bonus grants. HUD suggested that we revise our
conclusion to reflect the importance of the bonus grants. However, our
conclusion focuses on the base grants because of the use of cumulative
AIDS cases in determining these grants. HUD also noted that not all
grantees that receive bonus grants sustain the funding from year to year.
We have added text to note the instability of the bonus funding and that,
with respect to fiscal year 2006 funding, HUD's appropriation act included
a provision to mitigate the variability of incidence data by using data
reported over a 3-year period.

HUD also suggested that we use different terms to categorize how HOPWA
funding was allocated by grantees and provided us with updated information
on how grantees allocated fiscal year 2003 HOPWA grants. We have revised
the report based on this information.

HHS and HUD also provided technical comments, which we have incorporated
where appropriate.

We are sending copies of this report to the Secretary of Health and Human
Services, the Secretary of Housing and Urban Development, the Director of
the Centers for Disease Control and Prevention, the Administrator of the
Health Resources and Services Administration, and to interested
congressional committees. We will also make copies available to others
upon request. In addition, the report will be available on GAO's Web site
at http://www.gao.gov .

If you or your staff have any questions about this report, please contact
me at (202) 512-7119 or [email protected] . Contact points for our Offices
of Congressional Relations and Public Affairs may be found on the last
page of this report. GAO staff who made major contributions to this report
are listed in appendix XVII.

Marcia Crosse Director, Health Care

Appendix I: Objectives, Scope, and Methodology

Objectives

We assessed the distribution of funding for human immunodeficiency virus
(HIV) and acquired immunodeficiency syndrome (AIDS) under the Ryan White
Comprehensive AIDS Resources Emergency Act of 1990 (CARE Act) and the AIDS
Housing Opportunity Act's Housing Opportunities for Persons with AIDS
program (HOPWA). Specifically, we are reporting on (1) how CARE Act and
HOPWA funds are allocated by grantees among the types of services each
program supports; (2) the extent of funding distribution differences among
CARE Act and HOPWA grantees, and how CARE Act and HOPWA funding-formula
provisions contribute to these difference; and (3) what distribution
differences would result from using HIV cases in CARE Act and HOPWA
funding formulas.

Scope and Methodology

To report on these three objectives, we reviewed the CARE Act of 1990, as
well as the 1996 and 2000 CARE Act amendments, the AIDS Housing
Opportunity Act, Health Resources and Services Administration (HRSA) and
Department of Housing and Urban Development (HUD) documents on CARE Act
and HOPWA funding, HUD memoranda, Institute of Medicine reports on the
CARE Act, and other related reports. We interviewed officials from HRSA,
the Centers for Disease Control and Prevention (CDC), HUD, and the
National Alliance of State and Territorial AIDS Directors. We received
information from state government officials regarding their HIV
case-reporting systems. Details on the scope of our work and the methods
to address each objective follow.

Allocation of CARE Act and HOPWA Funds among Service Categories

To determine how grantees allocate CARE Act and HOPWA funds by types of
service, we obtained information on the allocation of these funds from
HRSA and HUD. 1 HRSA provided information on grantees' allocation of CARE
Act Titles I and II funds for fiscal year 2003, and Title III allocations
for fiscal year 2002. HRSA also provided funding amounts for its HIV/AIDS
Dental Reimbursement Program, Community-Based Dental Partnership grants,
Special Projects of National Significance, and AIDS Education and Training
Centers program for fiscal year 2003. HUD provided HOPWA allocation data
for fiscal year 2003, these being the most recently available data. We
analyzed these data and, where available, calculated the percentage of the
total amount each service category represented. To assess the reliability
of HRSA and HUD data on the allocations of CARE Act and HOPWA grant funds,
we interviewed agency officials about the data and reviewed relevant
documentation. We determined that the data were sufficiently reliable for
the purposes of our report.

Funding-formula Provisions

We examined the effect of specific funding-formula provisions on CARE Act
and HOPWA grants. We first assessed the use of 2- and 5-year cumulative
counts of AIDS cases and the use of estimated living AIDS cases (ELC) in
CARE Act programs by comparing these measures with living AIDS case counts
received from CDC. 2 We then examined the following CARE Act formula
provisions: the counting of ELCs in eligible metropolitan areas (EMA) for
both Title I and Title II funding, the tiered allocation of Emerging
Communities funding, the Title I hold-harmless provision, the Title I
grandfathering clause, and the Title II hold-harmless provision funded
from amounts available for Severe Need grants. 3 To examine the effect of
each provision on the CARE Act and HOPWA grant amounts, we measured
differences on a per case basis, by the amount of funding received, or
both. We calculated each grantee's percentage of the total number of AIDS
cases in all relevant jurisdictions, and we used these percentages to
determine the funding each grantee would have received. We then compared
these amounts with what was actually received to show the effect of a
provision in the formula. In addition, we examined the effect of using
living AIDS cases instead of cumulative cases in making HOPWA base grant
distributions by comparing the actual funding distributions with simulated
distributions using living AIDS cases. We also assessed the effect of
HOPWA bonus grants on funding for eligible metropolitan statistical areas
(EMSA) by examining the size of these grants and which EMSAs received
them.

To conduct our analyses of the effect of funding-formula provisions on
CARE Act and HOPWA funding and programs in the states, including the
District of Columbia, Puerto Rico, and metropolitan areas, we obtained
fiscal year 2004 funding data and AIDS case counts from HRSA and HUD, and
supplemented this information with additional AIDS case-count data from
CDC. Fiscal year 2004 data were the latest data available at the time of
our review. We limited our CARE Act analyses to Titles I and II because
grants under other parts of the Act are not formula-driven. Similarly, our
HOPWA analyses are also limited to the parts of the program that are
formula-based, namely, the base and bonus grants.

Our analyses of funding provisions take into consideration that CARE Act
and HOPWA formula grants use different measures of the number of AIDS
cases to determine grant amounts. There are three measures used for CARE
Act grants-reported AIDS cases over 2 years, reported AIDS cases over 5
years, and ELCs. HRSA calculates a jurisdiction's ELCs by using data from
CDC on the reported AIDS case counts for the last 10 years and weighting
those numbers to account for the likelihood of deaths. HOPWA uses two
measures-total AIDS cases reported in the jurisdiction since the beginning
of the epidemic in 1981 and AIDS incidence rates.

In our analyses of the funding formulas, we used the measure of AIDS cases
that is used to determine funding in a particular grant program in order
to show the effect of different formula provisions on fund distribution.
We also compared the AIDS data used for funding formulas with data on
living AIDS cases to assess the effect of not using living AIDS cases on
funding allocations. For the CARE Act, we used the measure of living AIDS
cases that is required by law to be used by the program when distributing
Title I, Title II, and ADAP base grants, that is, the number of ELCs based
on 10 years of reported cases and survival rates. In the absence of a
measure of living AIDS cases for HOPWA funding, we used a measure of
living AIDS cases calculated by subtracting the number of reported deaths
among AIDS cases in a jurisdiction from the number of reported cases. This
measure of living AIDS cases is used for illustrative purposes only.

In our analysis of counting ELCs in EMAs for both Title I and Title II
CARE Act funding, we aggregated Title I and Title II funding received by
each of the states and Puerto Rico. Because some EMAs cross state
boundaries, we apportioned Title I funding among states according to the
proportionate share of an EMA's ELCs in each state. For example,
approximately 96 percent of the ELCs in the Boston EMA are in
Massachusetts and 4 percent are in New Hampshire. Consequently, we
allocated 96 percent of the Boston EMA's funding to Massachusetts and 4
percent to New Hampshire. We then compared the combined total Title I and
Title II funding received by all Title II grantees.

To examine the effect of using living AIDS case counts on funding for
HOPWA base grants, we estimated the amount of funding grantees would have
received by determining the number of living AIDS cases in each
jurisdiction. CDC provided us with living AIDS cases counts for states,
Puerto Rico, and EMSAs. To determine each grantee's number of living AIDS
cases, we subtracted the number of living AIDS cases in EMSAs in a state
from the total number of living AIDS cases in the state. 4 When an EMSA
crossed state boundaries, we used information from CDC to determine the
number of living AIDS cases in each state within the EMSA. For example,
the Memphis EMSA covers parts of Arkansas, Mississippi, and Tennessee. We
obtained the living AIDS case counts for each of the states in the Memphis
EMSA. We then subtracted the number of living AIDS cases from Arkansas in
the Memphis EMSA from the Arkansas state total, and did comparable
calculations for the cases from the other two states. After doing similar
calculations for all EMSAs that crossed state boundaries, we had living
AIDS case counts for all HOPWA grantees. We then calculated each grantee's
percentage of the total number of living AIDS cases in all jurisdictions
and simulated the HOPWA base grant funding allocations according to this
percentage. We then compared the base funding received using cumulative
AIDS case counts with the simulated funding allocations using living AIDS
cases.

The dates of the AIDS case counts used in our analyses varied by program.
Depending on the grant, formula allocations under the CARE Act are based
on the number of ELCs in a jurisdiction as of June 30 preceding the start
of the fiscal year for which the award is to be made or on the number of
reported AIDS cases in either the most recent 2 or 5 calendar years. HOPWA
eligibility is based on the number of cumulative AIDS cases as of March 31
preceding the start of the fiscal year. Where appropriate, we used ELCs as
of June 30, 2003, to estimate the effect of formula provisions on CARE Act
funding for fiscal year 2004, which began on October 1, 2003. For other
CARE Act grants, we used reported cases for the appropriate calendar-year
period. We used AIDS case counts as of March 31, 2003, to estimate the
effect of formula provisions on HOPWA funding for fiscal year 2004.

We used funding per AIDS case 5 to illustrate the effect of certain
funding-formula provisions on the distribution of CARE Act and HOPWA
funds. There are other considerations that could be included in funding
formulas. For example, differing health care and housing costs across
regions and differences in grantees' capacities to fund services from
local resources could be used as bases for distributing program funds and
to justify deviations from proportional funding per case. 6 Without such
considerations, regions with the same funding and the same number of AIDS
cases could not treat the same number of patients. Currently, these
considerations are not taken into account when awarding formula grants
under either the CARE Act or HOPWA.

To analyze the effect of retaining the current EMA boundaries, we reviewed
documents pertaining to the Office of Management and Budget's (OMB) 2004
metropolitan boundary definitions. In particular, we relied on information
generated in our June 2004 report on metropolitan statistical areas (MSA)
that reported on the process used to develop the 2000 standards and how
the 2000 standards differ from the 1990 standards. 7 Before each decennial
census, OMB reviews the standards used in defining the boundaries of these
statistical areas to ensure their continued usefulness and relevance and,
if warranted, revises them. OMB had determined that a more fundamental
examination of the standards was required for 2000, and advisory groups
were formed to look at the standards. These groups suggested OMB consider
defining less-populated areas, which had been statistically unrecognized.
The 2000 standards differ from the 1990 standards in many ways, and the
Census Bureau and OMB have stated that the new standards are simpler and
more transparent.

To demonstrate the effect on the current boundaries of the 51 CARE Act
Title I EMAs if OMB's 2004 definitions of MSAs were used to establish EMA
boundaries, we compared the boundaries of existing EMAs with the new MSA
boundaries that could be created using the new definitions. Because most
EMA boundaries include portions of more than one new metropolitan area,
for our analysis we chose two decision rules to serve as a basis for
selecting new metropolitan areas to be compared with the existing EMAs. 8
First, we assumed there would be no change in eligibility of the current
51 Title I EMAs. Second, since the number of ELCs within an EMA would
change if its boundaries were revised, we chose whatever combination of
the newly defined metropolitan areas 9 would result in the least change to
the numbers of ELCs within the EMA's boundaries. The results of our method
are shown in appendix VII, which lists each of the existing EMAs together
with the corresponding new areas, the number of counties constituting the
metropolitan areas, and the number of ELCs contained within those areas.

To assess the reliability of the data on HRSA's and HUD's distribution of
CARE Act and HOPWA funds, we asked agency officials about how the data
were developed and reported. We also reviewed relevant documentation. We
determined the data were sufficiently reliable for the purposes of our
report.

Use of HIV Cases in Formulas

We examined how CARE Act and HOPWA fiscal year 2004 allocations would have
been affected by using HIV cases in addition to living AIDS cases to
determine funding. We undertook our analyses in light of the statutory
requirement that HIV cases be used in CARE Act funding formulas not later
than fiscal year 2007. 10 We examined the effect of using HIV cases in
addition to living AIDS cases on formula funding for CARE Act Title I,
Title II, and ADAP base grants, and HOPWA base grants in the states,
Puerto Rico, and metropolitan areas. 11 We limited our analyses to these
grants because they constitute the majority of the CARE Act and HOPWA
formula funding. For the CARE Act, we used the measure of living AIDS
cases that is required by law to be used by the program when distributing
Title I, Title II, and ADAP base grants, that is, the number of ELCs based
on 10 years of reported cases and survival rates. In the absence of a
measure of living AIDS cases for HOPWA funding, we used a measure of
living AIDS cases calculated by subtracting the number of reported deaths
among AIDS cases in a jurisdiction from the number of reported cases. This
measure of living AIDS cases is used for illustrative purposes only. We
used fiscal year 2004 allocations, which were based on case counts
reported as of June 30, 2003, for the CARE Act and as of March 31, 2003,
for HOPWA. As of these dates there were 35 jurisdictions 12 from which CDC
accepted HIV data and 17 without CDC-approved HIV data. CDC will only
accept name-based case counts as no code-based system has yet met CDC's
quality criteria. 13

Because CDC did not accept HIV case counts from 17 jurisdictions, we
conducted our analysis using two approaches to measure total HIV/AIDS
cases for purposes of formula calculations. Under the first approach, we
used HIV and live AIDS case counts for the 35 jurisdictions from which CDC
accepted HIV data. 14 Because CDC did not accept the HIV case counts from
the other 17 jurisdictions, we used only the live AIDS case counts
received by CDC for these grantees. Consequently, for some grantees we
used HIV and AIDS case counts, but for others we used only AIDS case
counts. This approach reflects the data that would have been used if
funding allocations were based on the HIV and AIDS case counts received by
CDC in time for determining fiscal year 2004 allocations. Under the second
approach, we used the same HIV and AIDS case counts as our first approach,
but supplemented these data with the code-based HIV case counts collected
by the grantees from which CDC did not receive HIV data. 15 We obtained
these HIV case counts directly from these jurisdictions. 16 These case
counts were collected and reported to us by public health authorities. We
also received information from them regarding their HIV case-reporting
systems.

For both approaches, we calculated the grantee's percentage of the total
number of HIV/AIDS cases relative to all grantees for that program and
estimated the fiscal year 2004 grants that each would have received. 17
CARE Act formula allocations were calculated both with certain
hold-harmless and minimum-grant provisions and again without those
provisions. 18 Eliminating hold-harmless and minimum-grant provisions was
done to show the full effect of distributing fiscal year 2004 funding
solely according to HIV/AIDS data available at that time. We also
estimated the effect of using HIV cases and living AIDS cases for HOPWA
base funding.

In our analyses of how the use of HIV cases would affect funding by
region, we use U.S. Census Bureau definitions to define regions of the
country. The Census Bureau divides the country into four regions:
Northeast, Midwest, South, and West. 19 Table 11 lists the four regions
and the jurisdictions that constitute them.

Table 11: U.S. Census Bureau Regions

Northeast            
Connecticut          New York       
Maine                Pennsylvania   
Massachusetts        Rhode Island   
New Hampshire        Vermont        
New Jersey           
Midwest              
Illinois             Missouri       
Indiana              Nebraska       
Iowa                 North Dakota   
Kansas               Ohio           
Michigan             South Dakota   
Minnesota            Wisconsin      
South                
Alabama              Mississippi    
Arkansas             North Carolina 
Delaware             Oklahoma       
District of Columbia South Carolina 
Florida              Tennessee      
Georgia              Texas          
Kentucky             Virginia       
Louisiana            West Virginia  
Maryland             
West                 
Alaska               Nevada         
Arizona              New Mexico     
California           Oregon         
Colorado             Utah           
Hawaii               Washington     
Idaho                Wyoming        
Montana              

Source: U.S. Census Bureau.

Our analyses of the effect of using HIV case counts for determining CARE
Act and HOPWA funding rely on data whose reliability has been questioned.
In June 2004, the Secretary of Health and Human Services determined that
because of the problems associated with these data, they should not
currently be used in determining CARE Act funding. We used these data in
our analyses to give a general indication of the effect of using HIV cases
in future formula allocations as required by the CARE Act. By using
HIV/AIDS counts in determining CARE Act and HOPWA funding, the number of
persons on which funding is based would increase. The effect on individual
grantees would depend on the number of reported HIV cases in the
jurisdiction compared with the number reported in other jurisdictions. The
extent to which the use of HIV cases could affect formula allocations
cannot be determined by these analyses because jurisdictions use different
methods to identify HIV cases, and it is unclear to what degree the
resulting case counts are comparable. However, we think our approaches in
these analyses are informative in light of the statutory requirement that
HIV cases be used in CARE Act funding formulas not later than fiscal year
2007.

To assess the reliability of the HIV and AIDS case-count data, we asked
HRSA, HUD, CDC, state, and local officials a series of questions about how
the data were collected and the methods used to ensure their accuracy. We
asked state and local officials about their HIV data only when they were
not accepted by CDC. On the basis of the information provided regarding
the verification of the reliability of these data, we determined these
data to be sufficiently reliable for the purposes of our analyses.

Our analyses do not include the different costs of treating patients with
HIV and AIDS. The cost of serving persons who have HIV and AIDS can vary
substantially, depending on the stage of the disease. Patients whose
disease has progressed to AIDS often require more expensive drug therapies
and more intensive care than those whose disease has not progressed to
AIDS. One study found that the average annual cost of treating an HIV
patient was about $18,000 per year. However, the cost ranged from about
$14,000 per year for well patients with HIV to $34,000 per year for
patients with advanced-stage AIDS. 20

We performed our work from July 2004 through February 2006, in accordance
with generally accepted government auditing standards.

Appendix II: CARE Act Title I Awards, Fiscal Year 2004 Appendix II: CARE
Act Title I Awards, Fiscal Year 2004

Eligible metropolitan area             Base award    Supplemental award     Minority AIDS  Total Title I award   Total Title I 
                                                                         Initiative award                       award per ELCa 
Atlanta, Ga.                           $9,268,937            $7,518,391        $1,552,404          $18,339,732          $2,417 
Austin, Tex.                            2,016,473             1,559,617           224,430            3,800,520           2,302 
Baltimore, Md.                         10,195,952             7,615,994         1,898,933           19,710,879           2,361 
Bergen-Passaic, N.J.b                   2,605,497             2,002,220           206,987            4,814,704           2,306 
Boston, Mass.b, c                       7,434,884             6,630,052           783,761           14,848,697           2,459 
Caguas, P.R.                              935,565               735,726           145,356            1,816,647           2,372 
Chicago, Ill.                          12,801,123            10,363,895         2,261,742           25,426,760           2,426 
Cleveland, Ohiob                        1,850,098             1,379,848           256,990            3,486,936           2,308 
Dallas, Tex                             6,425,600             5,378,653         1,016,330           12,820,583           2,437 
Denver, Colo.b                          2,440,655             1,843,081           245,361            4,529,097           2,273 
Detroit, Mich.                          4,382,256             3,427,753           780,272            8,590,281           2,394 
District of Columbiac                  14,431,645             9,840,164         2,679,205           26,951,014           2,281 
Dutchess County, N.Y.                     639,995               512,173            79,074            1,231,242           2,350 
Fort Lauderdale, Fla.                   7,330,631             6,349,097         1,069,822           14,749,550           2,457 
Fort Worth, Tex.                        1,805,177             1,386,868           181,405            3,373,450           2,282 
Hartford, Conn.                         2,386,547             1,899,397           266,293            4,552,237           2,330 
Houston, Tex.                           9,416,722             8,472,252         1,239,598           19,128,572           2,481 
Jacksonville, Fla.b                     2,517,844             1,873,132           472,117            4,863,093           2,371 
Jersey City, N.J.b                      3,022,562             2,548,825           312,807            5,884,194           2,424 
Kansas City, Mo.b, c                    1,716,152             1,358,374           166,287            3,240,813           2,503 
Las Vegas, Nev.c                        2,375,554             1,832,717           265,130            4,473,401           2,300 
Los Angeles, Calif.                    18,540,316            16,153,706         1,950,099           36,644,121           2,414 
Miami, Fla.                            12,806,009            10,268,761         2,465,241           25,540,011           2,436 
Middlesex-Somerset-Hunterdon,           1,520,364               988,206           215,127            2,723,697           2,200 
N.J.b                                                                                                          
Minneapolis-St. Paul, Minn.b,           1,587,346             1,328,653           177,916            3,093,915           2,432 
c                                                                                                              
Nassau-Suffolk, N.Y.b                   3,182,104             2,402,225           367,460            5,951,789           2,300 
New Haven, Conn.b                       3,639,492             3,012,393           417,463            7,069,348           2,400 
New Orleans, La.                        3,852,184             2,239,460           695,384            6,787,028           2,152 
New York, N.Y.                         60,276,790            52,106,068         9,720,259          122,103,117           2,474 
Newark, N.J.b                           8,151,371             6,076,957         1,083,776           15,312,104           2,297 
Norfolk, Va.c                           2,732,193             1,639,148           448,860            4,820,201           2,155 
Oakland, Calif.b                        3,534,076             2,614,717           462,814            6,611,607           2,318 
Orange County, Calif.                   2,666,239             2,282,192           284,898            5,233,329           2,397 
Orlando, Fla.                           4,021,954             3,028,863           770,969            7,821,786           2,375 
Philadelphia, Pa.c                     12,038,992            10,407,066         2,002,427           24,448,485           2,480 
Phoenix, Ariz.                          3,480,889             2,975,380           358,158            6,814,427           2,391 
Ponce, P.R.                             1,414,340             1,002,813           301,178            2,718,331           2,347 
Portland, Oreg.c                        1,889,451             1,572,205           105,819            3,567,475           2,306 
Riverside-San Bernardino,               3,913,252             2,613,404           296,527            6,823,183           2,130 
Calif.                                                                                                         
Sacramento, Calif.b                     1,558,276             1,328,376            81,399            2,968,051           2,382 
St. Louis, Mo.c                         2,412,195             1,646,152           312,807    4,371,154Appendix           2,213 
                                                                                            VI: Total CARE Act 
                                                                                          Title I and Title II 
                                                                                          Funding by State and 
                                                                                             Territory, Fiscal 
                                                                                                     Year 2004 
San Antonio, Tex. Total Title 2,097,083ELCsaELCsa   1,400,297Percent of      336,063Total            3,833,443    2,233Alabama 
I and Title II awards Total                        ELCs in EMAs Percent Title I and Title                      
Title I and Title II awards                             of ELCs in EMAs     II awards per                      
                                                                         ELCTotal Title I                      
                                                                             and Title II                      
                                                                           awards per ELC                      
San Diego, Calif. 3,320               5,201,7920%       4,554,583$3,657           531,422    10,287,797Alaskab    2,416974,705 
San Francisco, Calif.b0           16,171,6074,351            13,199,079    479,094Arizona 29,849,78018,635,537      4,1373,978 
San Jose, Calif.b4,685                  1,411,781     1,069,179Arkansas  175,5904,933,831       2,656,5501,466          2,3180 
San Juan, P.R.b               8,139,880California  5,255,408223,607,373   1,337,27742,479       14,732,56588.9      2,2225,264 
Santa Rosa, Calif.bColorado     611,31212,949,158          469,3702,658        26,74675.0       1,107,4284,872           2,298 
Seattle, Wash.b26,797,308          3,024,1725,363         2,605,64291.4      212,8014,997            5,842,615   2,367Delaware 
Tampa-St. Petersburg,                  4,777,6960        3,348,9203,518           593,053 8,719,669District of 2,25033,288,417 
Fla.b1,518                                                                                            Columbia 
Vineland-Millville-Bridgeton,        473,8895,074               297,261     76,748Florida   847,898182,771,752     2,18538,101 
N.J. 100.0                                                                                                     
West Palm Beach, Fla.b4,797             4,577,648      3,964,724Georgia 866,32354,483,301      9,408,69511,226       2,51567.6 
Totald                         $305,704,561Hawaii $246,379,4373,298,130    $43,258,002988        $595,342,0000           3,338 

Source: GAO analysis of HRSA data. Idahob

Notes: HRSA has awarded Minority AIDS Initiative grants to EMAs. HRSA
characterizes Minority AIDS Initiative grants to EMAs as Title I grants.
1,019,352

aHRSA calculates a jurisdiction's ELCs by using data from CDC on the
reported AIDS case counts for the last 10 years and weighting those
numbers to account for the likelihood of death. The average total Title I
award per ELC was $2,380. 220

bEMA received hold-harmless funding that is included in base award. 0

cEMA boundaries include jurisdictions in more than one state. 4,633

dIndividual entries may not sum to totals because of rounding.

                                              State/territory State/territory

                                                                  $12,142,447

                                                                          224

                                                                         73.5

                                                                        3,366

                                                                  Connecticut

                                                                    5,340,795

                                                                        6,561

                                                                         77.3

                                                                        4,853

Illinois

Appendix III: CARE Act Title II Awards, Fiscal Year 2004 Appendix III:
CARE Act Title II Awards, Fiscal Year 2004 60,837,359

12,203

Grantee                      Base grant award         ADAP base grant award                   Minority AIDS Initiative award          Emerging            ADAP Severe Need award                    Total Title II award           Total Title II award per ELCa 
                                                                                                                             Communities award                                                                           
Alabama Iowa             $4,042,811 2,067,375                 $7,004,635619                                         $77,8280     $192,2603,340                          $824,913                       $12,142,447Kansas                         $3,6573,881,999 
Alaskab34.2                     500,000 4,048                       472,602                                    2,103Kentucky             1,937                          974,7050                              4,3513,702                               7,170,005 
Arizona Louisiana        3,201,547 29,740,454                8,392,9036,555                                       54,16448.1                                    11,648,614Maineb                          2,9281,333,909                                   4,537 
Arkansas 0                    1,785,169 3,377                     3,116,716                                   31,946Maryland            12,203                     4,933,83193.6                              3,3665,018                              61,230,030 
California              31,236,233 34,432,147               89,623,4656,960                                      565,82983.2                                 121,425,527Michigan                         2,85824,046,130                                   4,947 
Massachusetts                                                                                                                                                                                                            
Colorado 68.8                 2,117,525 4,611                     5,607,928                                  34,181Minnesota     660,427 1,427                     8,420,06188.7                              3,1685,003                               7,139,028 
Connecticut               3,779,591 9,454,950               11,315,0182,747                                          81,1140                                  15,175,723Missouri                         2,83016,501,234                                   3,442 
Mississippi                                                                                                                                                                                                              
Delaware 76.8                 1,848,490 4,699                     3,202,722                                   39,177Montanab    250,406847,196                               147                              5,340,7950                              3,5185,763 
District of Columbia      4,305,124 1,887,660                 13,842,594525                                         175,7700                                    18,323,488Nevada                         2,79310,757,214                                   3,596 
Nebraska                                                                                                                                                                                                                 
Florida 83.3                 29,860,865 4,789                    80,386,630                            893,442New Hampshireb  528,0111,864,452                               358                         111,668,94869.0                              2,9315,208 
Georgia New Jersey       9,408,492 80,222,837              23,684,95116,531                                      260,82884.8         2,789,298              36,143,569New Mexico                          3,2203,338,463                                   4,853 
Hawaii 0                      1,203,101 3,400                     2,084,512                                   10,517New York            59,226                     3,298,13088.6                              3,3385,041                             298,549,361 
IdahobNorth Carolina       500,000 22,668,734                  464,1636,083                                           5260.1            54,663            1,019,352North Dakotac                            4,633292,543                                   3,727 
Illinois 0                    8,837,193 6,803                    25,746,254                                      287,121Ohio             5,171                    34,870,56829.2                              2,8583,916                              20,249,202 
Indiana Oklahoma          3,768,825 6,343,022                6,529,9241,687                                          47,1960    1,057,0053,760                                                          11,402,950Oregon                          3,6849,084,990 
Iowa 68.9                       753,765 4,536                     1,305,985                                7,625Pennsylvania            12,840                     2,067,37567.4                              3,3404,655                              59,766,256 
Kansas Puerto Rico       1,007,120 53,026,882               2,045,49510,711                                        8,54579.9                               3,061,160Rhode Island                          3,1923,189,276                                   4,951 
Kentucky 0                    2,358,712 3,520                     4,086,741                             22,875South Carolina 220,39520,705,328                     481,282 5,563                              7,170,0050                              3,7023,722 
Louisiana South             6,211,002 705,706                  13,829,93597                                         192,0720    1,091,7127,275                         1,628,705                     22,953,426Tennessee                         3,50221,178,234 
Dakotab                                                                                                                                                                                                                  
Maineb0                         500,000 4,169                       833,383                                         526Texas     36,525 23,922                     1,370,43474.5                              3,4694,973                             118,965,938 
Maryland Utah             8,446,358 3,235,191                 25,746,254882                                         317,3590                                  34,509,971Vermontb                            2,828883,059                                   3,668 
Massachusetts 0               5,223,382 4,879                    14,684,416                                   99,257Virginia 183,81932,149,863                             6,872                          20,190,87463.2                              2,9014,678 
Michigan Washington      4,335,555 17,349,313               11,002,7633,776                                      117,53169.8                             15,455,849West Virginia                          2,9642,335,062                                   4,595 
Minnesota 11.3                1,026,762 3,778                     3,010,727                                  22,218Wisconsin             1,507                      4,059,7070.4                              2,8453,718                               5,603,506 
Mississippi Wyomingc        3,345,060 360,347                   5,795,70376                                          88,4770      225,7104,741                                     9,454,950Source: GAO analysis of HRSA  3,442Notes: Our analysis is limited to 
                                                                                                                                                                                                                   data.             the states and Puerto Rico. 
Missouri bState              2,783,489 cState                     7,409,723                                           56,925    Table 12: EMAs 10,250,137HRSA 2004 EMA HRSA 2004      2,919GAO-identified comparable OMB      Appendix VII: HRSA's Title I EMAs, 
received a Title II  received a Title II base                                                                                with Service Area                               EMA            newly defined 2004 MSA(s) or   GAO-Identified Set of Comparable 2004 
base award of          award of $200,000, the                                                                                          Changes                                     MDIV(s)aGAO-identified comparable OMB     OMB-Defined Metropolitan Areas, and 
$500,000, the        minimum it could receive                                                                                                                                      newly defined 2004 MSA(s) or MDIV(s)a    Changes Appendix VII: HRSA's Title I 
minimum it could       based on the number of                                                                                                                                                                             EMAs, GAO-Identified Set of Comparable 
receive based on the       ELCs in the state.                                                                                                                                                                               2004 OMB-Defined Metropolitan Areas, 
number of ELCs in                                                                                                                                                                                                                                    and Changes 
the state.                                                                                                                                                                                                               
Montanab              500,000 OMB's 1993 full  310,145Number of counties in                     526ELCs in EMAs ELCs in EMAs         Number of  810,671ELCs in EMAs ELCs in EMAs   5,515Decrease in counties Decrease in   OMB's 2004 full title of metropolitan 
                        title of metropolitan EMA Number of counties in EMA                                                    counties in EMA                                                                  counties        area(s) OMB's 2004 full title of 
                         area OMB's 1993 full                                                                                        Number of                                                                                              metropolitan area(s) 
                        title of metropolitan                                                                                  counties in EMA                                                                           
                                         area                                                                                                                                                                            
Nebraska Change in                    639,300     1,107,661Atlanta, Ga. MSA                                         10,25420           130,445                       1,887,66028                              3,5967,663                                   7,589 
ELCs (percent)Change                                                                                                             Atlanta-Sandy                                                                           
in ELCs (percent)                                                                                                                  Springs-Ga.                                                                           
                                                                                                                             Marietta, Ga. MSA                                                                           
Nevada 8                         1,684,896 1%                     4,738,678 32,735Boston-Worcester-Lawrence-Lowell-Brockton,             6,038 6,456,309Boston-Cambridge-Quincy,                                  2,8759                                      10 
                                                                                                            Mass.-N.H. NECMA                     Mass-N.H. MSA; Worcester, Mass.                                         
                                                                                                                                                MSA; and Manchester-Nashua, N.H.                                         
                                                                                                                                                                             MSA                                         
New Hampshireb1                     500,000 0                     755,319-9                                            1,709                 9                   1,257,02810,481    3,511Chicago-Naperville-Joliet, Ill.                      Chicago, Ill. PMSA 
                                                                                                                                                                                   MDIV; and Lake County-Kenosha County, 
                                                                                                                                                                                                          Ill.-Wis. MDIV 
New Jersey 10,534                12,302,631 0                   34,877,5981                                         279,3651           181,943     Cleveland-Lorain-Elyria, Ohio                             47,641,5376                              2,8821,511 
                                                                                                                                                                            PMSA                                         
New Mexico 5                  1,195,795 1,484                    2,127,0241                                          15,6440                          3,338,463Dallas, Tex. PMSA                                  3,4008                                      -2 
New York                         42,659,431 8              124,956,7845,229                                       1,252,4751          394,5231                                -1                             169,263,213                 2,858Denver, Colo. PMSA 
Dallas-Plano-Irving,                                                                                                                                                                                                     
Tex. MDIV                                                                                                                                                                                                                
North Carolina 1,993 7,403,985 Denver-Aurora,                  12,834,09510                                     197,5932,017          708,7030                       1,511,429 5                             22,655,8051                                   3,724 
                                   Colo./ MSA                                                                                                                                                                            
North Dakotac6                  200,000 3,588 92,543Detroit-Warren-Livonia,                                               07             3,601                                 0                                292,5431                                 6,8030b 
                                                Mich. MSA and Monroe, Mich.                                                                                                                                              
                                                                        MSA                                                                                                                                              
Ohio Dutchess                     5,448,305 1                 10,909,930524 67,968Poughkeepsie-Newburgh-Middletown, N.Y. MSA          336,0632                             1,010                             16,762,2660                                  3,2421 
County, N.Y. PMSA                                                                                                                                                                                                        
Oklahoma                       2,054,284 Fort                    3,655,7074                                      23,7951,478       190,071Fort                         419,165 4                          6,343,0221,475                                  3,7601 
                        Worth-Arlington, Tex.                                                                                 Worth-Arlington,                                                                           
                                         PMSA                                                                                        Tex. MDIV                                                                           
Oregon 0b                           1,664,149   4,225,989Houston, Tex. PMSA                                          12,4896             7,710  Houston-Sugar Land-Baytown, Tex.                             5,902,62710                              2,9478,106 
                                                                                                                                                                             MSA                                         
Pennsylvania 4                   10,779,206 5                    27,090,216                    258,856Jacksonville, Fla. MSA          188,1964                             2,051        38,316,474Jacksonville, Fla. MSA                                  2,9845 
Puerto Rico 0                     8,238,917 1                   22,598,3881                                          260,697      Kansas City,                      2,661,337 11                         33,759,3391,295         3,152Kansas City, Mo.-Kans. MSA 
                                                                                                                                 Mo.-Kans. MSA                                                                           
Rhode Island 1,305                1,103,249 0                    1,911,5064                                          14,4611           160,060         Las Vegas, Nev.-Ariz. MSA                              3,189,2763                              3,5201,945 
South Carolina 1              6,774,143 1,857                   11,736,9842                                         164,8580         647,118-5                         1,382,225 20,705,328Middlesex-Somerset-Hunterdon,                                  3,7223 
                                                                                                                                                                                                               N.J. PMSA 
South DakotabEdison,                500,000 4                  204,6542,217                                           1,0521                 2                                79                                 705,706               7,275New Orleans, La. MSA 
N.J. MDIV                                                                                                                                                                                                                
Tennessee 3,154                 6,185,987 New                   12,018,4387                                     122,5263,130        2,851,2831                                 0                            21,178,234-1                                   4,169 
                     Orleans-Metairie-Kenner,                                                                                                                                                                            
                                      La. MSA                                                                                                                                                                            
Texas 5                      19,125,106 6,665       50,471,351Newark-Union,                                         469,0706             6,735                       5,943,843 1                             76,009,3702                                  3,1771 
                                                              N.J.-Pa. MDIV                                                                                                                                              
Utah                             1,074,024 15                1,980,5652,237        7,099Virginia Beach-Norfolk-Newport News,         173,50316                             2,240                              3,235,1910                                  3,6681 
Norfolk-Virginia                                                                                                Va.-N.C. MSA                                                                                             
Beach-Newport News,                                                                                                                                                                                                      
VA-N.C. MSA                                                                                                                                                                                                              
Vermontb                500,000 Philadelphia,                      382,0079                                       1,0529,857 Philadelphia, Pa.                                 8                            883,0599,782                                  4,8791 
                                Pa.-N.J. PMSA                                                                                 MDIV and Camden,                                                                           
                                                                                                                                     N.J. MDIV                                                                           
Virginia -1                         5,929,341     14,498,751Ponce, P.R. MSA                                         145,0076      244,7791,158     1,707,470 Ponce, P.R. MSA and                             22,525,3487                              3,2781,202 
                                                                                                                                                                 Yauco, P.R. MSA                                         
Washington 1                      3,118,978 4                     7,966,718       35,890Portland-Vancouver, Oreg.-Wash. PMSA                 6                             1,547 11,121,586Portland-Vancouver-Beaverton,                                  2,9457 
                                                                                                                                                                                                         Oreg.-Wash. MSA 
West Virginia 0                     713,239 1                   1,303,8750b                                            4,733       Sacramento,                         153,553 3                          2,175,4001,246 3,520Sacramento-Arden-Arcade-Roseville, 
                                                                                                                                   Calif. PMSA                                                                                                        Calif. MSA 
Wisconsin 1,321                   1,831,726 0                    3,179,5141                                          28,7916           174,440   374,441 St. Louis, Mo.-Ill. MSA                             5,588,91212                              3,7091,975 
Wyomingc16                      200,000 1,993                      160,3470                                               04                 1                                              360,347San Antonio, Tex. MSA                                  4,7414 
Total San Antonio,             $284,712,863 8             $727,320,9291,750                                      $6,903,7970      $10,000,0004                     $20,759,721 2                          $1,049,697,310                   San Jose, Calif. PMSA 
Tex. MSA                                                                                                                                                                                                                 

Source: GAO analysis of HRSA data. 1,146

Notes: HRSA has awarded grants for Minority AIDS Initiative grants to
states and territories. HRSA characterizes Minority AIDS Initiative grants
to states and territories as Title II grants. San Jose-Sunnyvale-Santa
Clara, Calif. MSA

In addition to the grantees listed, American Samoa, the Federated States
of Micronesia, Guam, the Republic of the Marshall Islands, the
Commonwealth of the Northern Mariana Islands, the Republic of Palau, and
the Virgin Islands also received Title II funding ranging from a total of
$50,000 to $1,048,657. 2

aHRSA calculates a jurisdiction's ELCs by using data from CDC on the
reported AIDS case counts for the last 10 years and weighting those
numbers to account for the likelihood of death. The average total Title II
award per ELC was $3,559. 1,163

bState received a Title II base award of $500,000, the minimum it could
receive based on the number of ELCs in the state. 0

cState received a Title II base award of $200,000, the minimum it could
receive based on the number of ELCs in the state. 1

                                                                          959

                                                                          395

                                                                        5,215

                                                                        3,512

                                                                        2,246

                                                                          982

                                                                           43

                                                                        2,003

                                                                          906

                                                                        5,080

                                                                          181

                                                                          618

         aHRSA calculates a jurisdiction's ELCs by using data from CDC on the
          reported AIDS case counts for the last 10 years and weighting those
                              numbers to account for the likelihood of death.

                                                              Changes Changes

                                     Increase in countiesIncrease in counties

                                                                            0

                                                                        5,484

                                                                           10

                                            Cleveland-Elyria-Mentor, Ohio MSA

                                                                        5,261

                                                                            5

                                                          Detroit, Mich. PMSA

                                                                           93

                                                                            1

                                                                            0

                                                                        2,080

                                                                           15

                                                 Las Vegas-Paradise, Nev. MSA

                                                                        1,238

                                                                            8

                                                            Newark, N.J. PMSA

                                                                           0b

                                                                            0

                                                                            0

                                                                        1,548

                                                                            4

                                                      St. Louis, Mo.-Ill. MSA

                                                                        1,717

                                                                            1

1

Appendix IV: HOPWA Formula Grantees and Award Amounts, Fiscal Year 2004
Appendix IV: HOPWA Formula Grantees and Award Amounts, Fiscal Year 2004

Seattle-Bellevue-Everett, Wash. PMSA

Grantee        Base funding        Bonus fundinga Total formula Total formula funding per cumulative     Total formula 
                                                        funding                           AIDS caseb       funding per 
                                                                                                     living AIDS casec 
Alabama -1       $1,139,000          $1,139,00025   $230 11,816 $444Washington-Arlington-Alexandria,       Washington, 
                                                                                    D.C.-Va.-Md. MSA D.C.-Md.-Va-W.Va. 
                                                                                                                  PMSA 
Albany, N.Y.      429,000 3             429,000-1           230         497Bergen-Passaic, N.J. PMSA                 0 
11,732                                                                                               
Arizona 2,088   164,000 New         164,00053,867         230 0                                 4740                11 
                 York-White                                                                          
              Plains-Wayne,                                                                          
                  N.Y.-N.J.                                                                          
                       MDIV                                                                          
Arkansas            752,000          752,0002,427           230                                  418                 1 
               Jersey City,                                                                          
                  N.J. PMSA                                                                          
Atlanta, Ga.      4,262,000              $637,000     4,899,000         264 New York City, N.Y. PMSA              5738 
Augusta, Ga.        373,000               373,000           230                                  455 
Austin, Tex.      988,000 5            988,000San        230 41                             5207,724               766 
Caguas, P.R.                Juan-Caguas-Guaynabo,                                                    
PMSA                                     P.R. MSA                                                    
Baltimore,      3,940,000 4             3,996,000  7,936,000San                               463 30        1,0396,631 
Md. 9                                             Juan-Bayamon,                                      
                                                      P.R. PMSA                                      
Baton Rouge,        666,000             1,147,000     1,813,000                                  626             1,290 
La.                                                                                                  
Birmingham,         520,000            520,000275   230 160,694                                46117    Not applicable 
Ala. 239            158,952                                                                          
Boston, Mass.     1,829,000           1,829,00057    230 84,768                    563Not applicable       Subtotal of 
1                                                                                                      unchanged areas 
                                                                                                        (see table 13) 
Bridgeport,       752,000 0               27,0000      779,0000                                  238          476Total 
Conn. 84,768                                                                                         
Buffalo, N.Y.   472,000 Not        472,000245,462        230 17                                52353               332 
243,720          applicable                                                                          
California        3,042,000    3,042,000aWe chose  230 bPercent                                  518     Notes: HRSA's 
               Sources: GAO  whatever combination   change that                                       Title I EMAs are 
                analysis of  of the newly defined     rounds to                                         based on OMB's 
                 CDC, HRSA,    metropolitan areas     zero, but                                      1993 metropolitan 
              and OMB data.  that would result in      does not                                                   area 
                              the least change to    equal zero                                       definitions.This 
                              the numbers of ELCs      percent.                                       table uses OMB's 
                                 within the EMA's                                                      terminology for 
                                      boundaries.                                                    classifying types 
                                                                                                       of metropolitan 
                                                                                                                areas. 
                                                                                                      Specifically, it 
                                                                                                              includes 
                                                                                                          metropolitan 
                                                                                                      statistical area 
                                                                                                        (MSA), primary 
                                                                                                          metropolitan 
                                                                                                      statistical area 
                                                                                                           (PMSA), New 
                                                                                                        England county 
                                                                                                     metropolitan area 
                                                                                                          (NECMA), and 
                                                                                                          metropolitan 
                                                                                                      division (MDIV). 
                                                                                                        The terms used 
                                                                                                        and meaning of 
                                                                                                           those terms 
                                                                                                                differ 
                                                                                                       between1993 and 
                                                                                                       2004 because of 
                                                                                                     OMB's fundamental 
                                                                                                          revisions of 
                                                                                                          metropolitan 
                                                                                                         concepts. For 
                                                                                                               further 
                                                                                                      explanation, see 
                                                                                                           GAO-04-758. 
Cambridge,          659,000               659,000           230                                  518 
Mass.                                                                                                
Camden, N.J.        657,000               657,000           230                                  567 
Charleston,         411,000                 7,000       418,000                                  234               480 
S.C.                                                                                                 
Charlotte,          571,000               571,000           230                                  450 
N.C.                                                                                                 
Chicago, Ill.     5,622,000             2,716,000     8,338,000                                  341               805 
Cincinnati,         550,000               550,000           230                                  523 
Ohio                                                                                                 
Cleveland,          854,000               854,000           230                                  479 
Ohio                                                                                                 
Colorado            366,000               366,000           230                                  462 
Columbia,           626,000               644,000     1,270,000                                  466               824 
S.C.                                                                                                 
Columbus,           584,000               584,000           230                                  619 
Ohio                                                                                                 
Connecticut         251,000               251,000           230                                  479 
Dallas, Tex.      3,192,000             3,192,000           230                                  496 
Delaware            164,000               164,000           230                                  463 
Denver, Colo.     1,424,000             1,424,000           230                                  547 
Detroit,          1,624,000               355,000     1,979,000                                  280               749 
Mich.                                                                                                
District of       5,626,000             6,176,000    11,802,000                                  482               939 
Columbia                                                                                             
Florida           4,063,000             4,063,000           230                                  489 
Fort              3,337,000             2,903,000     6,240,000                                  430               954 
Lauderdale,                                                                                          
Fla.                                                                                                 
Fort Worth,         835,000               835,000           230                                  500 
Tex.                                                                                                 
Gaithersburg,       535,000               535,000           230                                  467 
Md.                                                                                                  
Georgia           1,515,000              HIV/AIDS     1,515,000                                  230               469 
                                  FundingHIV/AIDS                                                    
                                  FundingHIV/AIDS                                                    
                                  FundingHIV/AIDS                                                    
                                  FundingHIV/AIDS                                                    
                                  FundingHIV/AIDS                                                    
                                  FundingHIV/AIDS                                                    
                                  FundingHIV/AIDS                                                    
                                  FundingHIV/AIDS                                                    
                                  FundingHIV/AIDS                                                    
                                  FundingHIV/AIDS                                                    
                                  FundingHIV/AIDS                                                    
                                          Funding                                                    
Hartford,         1,023,000             1,023,000           230                                  460 
Conn.                                                                                                
Hawaii              181,000               181,000           230                                  439 
Honolulu,           452,000               452,000           230                                  571 
Hawaii                                                                                               
Houston, Tex.     5,068,000             5,068,000           230                                  591 
Illinois            864,000               864,000           230                                  466 
Indiana             836,000               836,000           230                                  500 
Indianapolis,       759,000               759,000           230                                  476 
Ind.                                                                                                 
Iowa                347,000               347,000           230                                  511 
Islip, N.Y.       1,660,000             1,660,000           230                                  577 
Jackson,            449,000               275,000       724,000                                  371               728 
Miss.                                                                                                
Jacksonville,     1,195,000               369,000     1,564,000                                  301               623 
Fla.                                                                                                 
Kansas              363,000               363,000           230                                  562 
Kansas City,        978,000               978,000           230                                  506 
Mo.                                                                                                  
Kentucky            423,000               423,000           230                                  418 
Las Vegas,          916,000               916,000           230                                  455 
Nev.                                                                                                 
Los Angeles,     10,476,000            10,476,000           230                                  622 
Calif.                                                                                               
Louisiana           940,000               940,000           230                                  488 
Louisville,         462,000               462,000           230                                  443 
Ky.                                                                                                  
Maryland            345,000               345,000           230                                  453 
Massachusetts       525,000               525,000           230                                  521 
Memphis,            920,000             1,214,000     2,134,000                                  533             1,000 
Tenn.                                                                                                
Miami, Fla.       6,149,000             4,566,000    10,715,000                                  400               934 
Michigan            911,000               911,000           230                                  546 
Milwaukee,          512,000               512,000           230                                  511 
Wis.                                                                                                 
Minneapolis,        839,000               839,000           230                                  508 
Minn.                                                                                                
Minnesota           110,000               110,000           230                                  529 
Mississippi         756,000               756,000           230                                  484 
Missouri            496,000               496,000           230                                  471 
Nashville,          737,000               737,000           230                                  387 
Tenn.                                                                                                
Nevada              238,000               238,000           230                                  499 
New Haven,          937,000               295,000     1,232,000                                  302               605 
Conn.                                                                                                
New Jersey        1,106,000                           1,106,000                                  230               593 
New Mexico          533,000               533,000           230                                  501 
New Orleans,      1,785,000             1,207,000     2,992,000                                  385               887 
La.                                                                                                  
New York          1,776,000             1,776,000           230                                  500 
New York,        33,487,000            26,868,000    60,355,000                                  414             1,099 
N.Y.                                                                                                 
Newark, N.J.      4,297,000               885,000     5,182,000                                  277               828 
North             2,082,000             2,082,000           230                                  437 
Carolina                                                                                             
Oakland,          2,006,000             2,006,000           230                                  595 
Calif.                                                                                               
Ohio              1,041,000             1,041,000           230                                  524 
Oklahoma            518,000               518,000           230                                  521 
Oklahoma            466,000               466,000           230                                  509 
City, Okla.                                                                                          
Orlando, Fla.     1,660,000             1,529,000     3,189,000                                  441               913 
Pennsylvania      1,540,000             1,540,000           230                                  445 
Philadelphia,     4,340,000             3,292,000     7,632,000                                  404               799 
Pa.                                                                                                  
Phoenix,          1,434,000             1,434,000           230                                  490 
Ariz.                                                                                                
Pittsburgh,         626,000               626,000           230                                  568 
Pa.                                                                                                  
Portland,         1,006,000             1,006,000           230                                  523 
Oreg.                                                                                                
Poughkeepsie,       604,000               604,000           230                                  556 
N.Y.                                                                                                 
Providence,         807,000               807,000           230                                  498 
R.I.                                                                                                 
Puerto Rico       1,748,000             1,748,000           230                                  584 
Richmond, Va.       692,000               692,000           230                                  527 
Riverside,        1,772,000             1,772,000           230                                  462 
Calif.                                                                                               
Rochester,          597,000               597,000           230                                  460 
N.Y.                                                                                                 
Sacramento,         844,000               844,000           230                                  574 
Calif.                                                                                               
St. Louis,        1,217,000             1,217,000           230                                  491 
Mo.                                                                                                  
Salt Lake           386,000               386,000           230                                  455 
City, Utah                                                                                           
San Antonio,      1,027,000             1,027,000           230                                  480 
Tex.                                                                                                 
San Diego,        2,683,000             2,683,000           230                                  522 
Calif.                                                                                               
San               6,698,000             1,864,000     8,562,000                                  294             1,130 
Francisco,                                                                                           
Calif.                                                                                               
San Jose,           792,000               792,000           230                                  538 
Calif.                                                                                               
San Juan,         4,585,000             2,555,000     7,140,000                                  358             1,000 
P.R.                                                                                                 
Santa Ana,        1,436,000             1,436,000           230                                  489 
Calif.                                                                                               
Sarasota,           397,000               397,000           230                                  501 
Fla.                                                                                                 
Seattle,          1,688,000             1,688,000           230                                  524 
Wash.                                                                                                
South             1,387,000             1,387,000           230                                  446 
Carolina                                                                                             
Springfield,        461,000               461,000           230                                  535 
Mass.                                                                                                
Tampa, Fla.       2,221,000               168,000     2,389,000                                  247               569 
Tennessee           739,000               739,000           230                                  438 
Texas             2,736,000             2,736,000           230                                  454 
Tucson, Ariz.       402,000               402,000           230                                  515 
Utah                120,000               120,000           230                                  467 
Virginia            640,000               640,000           230                                  499 
Virginia          1,022,000             1,022,000           230                                  505 
Beach, Va.                                                                                           
Wake County,        345,000                 7,000       352,000                                  234               408 
N.C.                                                                                                 
Warren, Mich.       405,000               405,000           230                                  571 
Washington          652,000               652,000           230                                  480 
West Palm         2,019,000             1,817,000     3,836,000                                  436               933 
Beach, Fla.                                                                                          
Wilmington,         566,000               232,000       798,000                                  325               624 
Del.                                                                                                 
Wisconsin           405,000               405,000           230                                  509 
Woodbridge,       1,462,000             1,462,000           230                                  627 
N.J.                                                                                                 
Worcester,          369,000               369,000           230                                  480 
Mass.                                                                                                
Total          $197,288,000           $65,751,000  $263,039,000                                      

Sources: GAO analysis of CDC and HUD data.

aBonus grants were awarded to EMSAs that have a higher-than-average per
capita incidence of AIDS over the previous year.

bThe average formula funding per cumulative AIDS case was $260.

cThe number of living AIDS cases was calculated by subtracting the number
of reported deaths among AIDS cases in a jurisdiction from the number of
reported cases. The average formula funding per living AIDS case was $573.

                                                                            0

                                                                           22

                                                                            2

                                                                            0

                                                                       49,352

                                                                            3

                                                    Subtotal of changed areas

                                                                           53

                                                                           57

                                                                          296

                                                                            1

Appendix V: HOPWA Base Funding Allocations Using Cumulative and Living
AIDS Cases, Fiscal Year 2004 Appendix V: HOPWA Base Funding Allocations
Using Cumulative and Living AIDS Cases, Fiscal Year 2004

Grantee        Base funding Cumulative        Percent of  Living AIDS casesa  Percent          Funding if      Difference in 
                            AIDS cases   cumulative AIDS                           of     allocated using           fundingb 
                                                   cases                       living   living AIDS cases 
                                                                                 AIDS                     
                                                                                cases                     
Alabama          $1,139,000      4,969             0.58%               2,568    0.70%          $1,378,278          -$239,278 
Albany, N.Y.        429,000      1,867              0.22                 864     0.24             463,720            -34,720 
Arizona             164,000        712              0.08                 346     0.09             185,703            -21,703 
Arkansas            752,000      3,274              0.38               1,799     0.49             965,546           -213,546 
Atlanta, Ga.      4,262,000     18,554              2.16               8,557     2.33           4,592,649           -330,649 
Augusta, Ga.        373,000      1,623              0.19                 819     0.22             439,568            -66,568 
Austin, Tex.        988,000      4,302              0.50               1,899     0.52           1,019,217            -31,217 
Baltimore,        3,940,000     17,150              2.00               7,641     2.08           4,101,020           -161,020 
Md.                                                                                                       
Baton Rouge,        666,000      2,898              0.34               1,405     0.38             754,081            -88,081 
La.                                                                                                       
Birmingham,         520,000      2,265              0.26               1,127     0.31             604,875            -84,875 
Ala.                                                                                                      
Boston, Mass.     1,829,000      7,960              0.93               3,248     0.88           1,743,242             85,758 
Bridgeport,         752,000      3,275              0.38               1,637     0.45             878,598           -126,598 
Conn.                                                                                                     
Buffalo, N.Y.       472,000      2,053              0.24                 902     0.25             484,115            -12,115 
California        3,042,000     13,240              1.54               5,870     1.60           3,150,502           -108,502 
Cambridge,          659,000      2,868              0.33               1,271     0.35             682,162            -23,162 
Mass.                                                                                                     
Camden, N.J.        657,000      2,861              0.33               1,159     0.32             622,050             34,950 
Charleston,         411,000      1,788              0.21                 870     0.24             466,940            -55,940 
S.C.                                                                                                      
Charlotte,          571,000      2,486              0.29               1,269     0.35             681,088           -110,088 
N.C.                                                                                                      
Chicago, Ill.     5,622,000     24,471              2.85              10,362     2.82           5,561,415             60,585 
Cincinnati,         550,000      2,394              0.28               1,051     0.29             564,085            -14,085 
Ohio                                                                                                      
Cleveland,          854,000      3,718              0.43               1,784     0.49             957,495           -103,495 
Ohio                                                                                                      
Colorado            366,000      1,595              0.19                 792     0.22             425,076            -59,076 
Columbia,           626,000      2,727              0.32               1,541     0.42             827,074           -201,074 
S.C.                                                                                                      
Columbus,           584,000      2,542              0.30                 944     0.26             506,657             77,343 
Ohio                                                                                                      
Connecticut         251,000      1,092              0.13                 524     0.14             281,237            -30,237 
Dallas, Tex.      3,192,000     13,895              1.62               6,436     1.75           3,454,282           -262,282 
Delaware            164,000        716              0.08                 354     0.10             189,996            -25,996 
Denver, Colo.     1,424,000      6,200              0.72               2,602     0.71           1,396,526             27,474 
Detroit,          1,624,000      7,068              0.82               2,641     0.72           1,417,458            206,542 
Mich.                                                                                                     
District of       5,626,000     24,490              2.85              12,570     3.42           6,746,476         -1,120,476 
Columbia                                                                                                  
Florida           4,063,000     17,686              2.06               8,306     2.26           4,457,934           -394,934 
Fort              3,337,000     14,527              1.69               6,541     1.78           3,510,636           -173,636 
Lauderdale,                                                                                               
Fla.                                                                                                      
Fort Worth,         835,000      3,635              0.42               1,670     0.45             896,310            -61,310 
Tex.                                                                                                      
Gaithersburg,       535,000      2,328              0.27               1,146     0.31             615,073            -80,073 
Md.                                                                                                       
Georgia           1,515,000      6,593              0.77               3,233     0.88           1,735,192           -220,192 
Hartford,         1,023,000      4,455              0.52               2,222     0.60           1,192,575           -169,575 
Conn.                                                                                                     
Hawaii              181,000        786              0.09                 412     0.11             221,126            -40,126 
Honolulu,           452,000      1,966              0.23                 791     0.22             424,540             27,460 
Hawaii                                                                                                    
Houston, Tex.     5,068,000     22,063              2.57               8,579     2.33           4,604,457            463,543 
Illinois            864,000      3,761              0.44               1,855     0.50             995,602           -131,602 
Indiana             836,000      3,638              0.42               1,673     0.46             897,920            -61,920 
Indianapolis,       759,000      3,302              0.38               1,595     0.43             856,056            -97,056 
Ind.                                                                                                      
Iowa                347,000      1,509              0.18                 679     0.18             364,428            -17,428 
Islip, N.Y.       1,660,000      7,226              0.84               2,877     0.78           1,544,122            115,878 
Jackson,            449,000      1,953              0.23                 994     0.27             533,492            -84,492 
Miss.                                                                                                     
Jacksonville,     1,195,000      5,202              0.61               2,509     0.68           1,346,612           -151,612 
Fla.                                                                                                      
Kansas              363,000      1,582              0.18                 646     0.18             346,716             16,284 
Kansas City,        978,000      4,256              0.50               1,933     0.53           1,037,465            -59,465 
Mo.                                                                                                       
Kentucky            423,000      1,841              0.21               1,011     0.28             542,616           -119,616 
Las Vegas,          916,000      3,986              0.46               2,014     0.55           1,080,939           -164,939 
Nev.                                                                                                      
Los Angeles,     10,476,000     45,601              5.31              16,834     4.58           9,035,018          1,440,982 
Calif.                                                                                                    
Louisiana           940,000      4,091              0.48               1,926     0.52           1,033,708            -93,708 
Louisville,         462,000      2,011              0.23               1,044     0.28             560,328            -98,328 
Ky.                                                                                                       
Maryland            345,000      1,501              0.17                 762     0.21             408,975            -63,975 
Massachusetts       525,000      2,287              0.27               1,007     0.27             540,469            -15,469 
Memphis,            920,000      4,006              0.47               2,133     0.58           1,144,808           -224,808 
Tenn.                                                                                                     
Miami, Fla.       6,149,000     26,766              3.12              11,477     3.12           6,159,849            -10,849 
Michigan            911,000      3,966              0.46               1,669     0.45             895,773             15,227 
Milwaukee,          512,000      2,228              0.26               1,001     0.27             537,249            -25,249 
Wis.                                                                                                      
Minneapolis,        839,000      3,654              0.43               1,650     0.45             885,576            -46,576 
Minn.                                                                                                     
Minnesota           110,000        480              0.06                 208     0.06             111,636             -1,636 
Mississippi         756,000      3,291              0.38               1,563     0.43             838,882            -82,882 
Missouri            496,000      2,157              0.25               1,053     0.29             565,158            -69,158 
Nashville,          737,000      3,208              0.37               1,902     0.52           1,020,827           -283,827 
Tenn.                                                                                                     
Nevada              238,000      1,034              0.12                 477     0.13             256,012            -18,012 
New Haven,          937,000      4,077              0.47               2,036     0.55           1,092,747           -155,747 
Conn.                                                                                                     
New Jersey        1,106,000      4,778              0.56               1,864     0.51           1,000,432            105,568 
New Mexico          533,000      2,319              0.27               1,064     0.29             571,062            -38,062 
New Orleans,      1,785,000      7,769              0.90               3,374     0.92           1,810,868            -25,868 
La.                                                                                                       
New York          1,776,000      7,730              0.90               3,553     0.97           1,906,940           -130,940 
New York,        33,487,000    145,769             16.97              54,900    14.94          29,465,516          4,021,484 
N.Y.                                                                                                      
Newark, N.J.      4,297,000     18,704              2.18               6,262     1.70           3,360,894            936,106 
North             2,082,000      9,065              1.06               4,761     1.30           2,555,288           -473,288 
Carolina                                                                                                  
Oakland,          2,006,000      8,731              1.02               3,374     0.92           1,810,868            195,132 
Calif.                                                                                                    
Ohio              1,041,000      4,533              0.53               1,985     0.54           1,065,374            -24,374 
Oklahoma            518,000      2,254              0.26                 995     0.27             534,029            -16,029 
Oklahoma            466,000      2,027              0.24                 916     0.25             491,629            -25,629 
City, Okla.                                                                                               
Orlando, Fla.     1,660,000      7,228              0.84               3,494     0.95           1,875,273           -215,273 
Pennsylvania      1,540,000      6,702              0.78               3,463     0.94           1,858,635           -318,635 
Philadelphia,     4,340,000     18,890              2.20               9,546     2.60           5,123,457           -783,457 
Pa.                                                                                                       
Phoenix,          1,434,000      6,244              0.73               2,924     0.80           1,569,347           -135,347 
Ariz.                                                                                                     
Pittsburgh,         626,000      2,723              0.32               1,103     0.30             591,994             34,006 
Pa.                                                                                                       
Portland,         1,006,000      4,378              0.51               1,925     0.52           1,033,172            -27,172 
Oreg.                                                                                                     
Poughkeepsie,       604,000      2,630              0.31               1,087     0.30             583,406             20,594 
N.Y.                                                                                                      
Providence,         807,000      3,514              0.41               1,622     0.44             870,548            -63,548 
R.I.                                                                                                      
Puerto Rico       1,748,000      7,608              0.89               2,995     0.81           1,607,454            140,546 
Richmond, Va.       692,000      3,012              0.35               1,312     0.36             704,167            -12,167 
Riverside,        1,772,000      7,714              0.90               3,834     1.04           2,057,756           -285,756 
Calif.                                                                                                    
Rochester,          597,000      2,599              0.30               1,297     0.35             696,116            -99,116 
N.Y.                                                                                                      
Sacramento,         844,000      3,676              0.43               1,470     0.40             788,967             55,033 
Calif.                                                                                                    
St. Louis,        1,217,000      5,297              0.62               2,481     0.67           1,331,584           -114,584 
Mo.                                                                                                       
Salt Lake           386,000      1,680              0.20                 849     0.23             455,669            -69,669 
City, Utah                                                                                                
San Antonio,      1,027,000      4,469     0.52Change in      2,138Change in     0.58    1,147,491Grantee     -120,491Dollar 
Tex. Appendix                              Title II base        Title I base                      Grantee      changebDollar 
XII:                                          funding if funding if HIV case                                         changeb 
Estimated                               CDC-accepted HIV     counts from all                              
CARE Act                                 case counts and   grantees and ELCs                              
Title II Base                          ELCs were used to        were used to                              
Funding                                       distribute  distribute funding                              
Changes from                             funding without             without                              
Use of HIV                             hold-harmless and   hold-harmless and                              
Case Counts                                minimum-grant       minimum-grant                              
and ELCs                               provisions Change   provisionsaChange                              
without                                 in Title II base     in Title I base                              
Hold-harmless                                 funding if funding if HIV case                              
                                        CDC-accepted HIV     counts from all                              
                                         case counts and   grantees and ELCs                              
                                       ELCs were used to        were used to                              
                                              distribute  distribute funding                              
                                         funding without             without                              
                                       hold-harmless and   hold-harmless and                              
                                           minimum-grant       minimum-grant                              
                                              provisions         provisionsa                              
San Diego,        2,683,000     11,677       1.36Alabama     5,136$2,550,000  1.4063% 2,756,555$2,010,000         -73,55550% 
Calif. Dollar       Percent                                                                               
changebDollar changePercent                                                                               
changeb              change                                                                               
San               6,698,000  29,156-54      3.40-290,000            7,577-58     2.06    4,066,671Arizona 2,631,3291,220,000 
Francisco,         -270,000                                                                               
Calif.                                                                                                    
Alaskac                                                                                                   
San Jose,        792,000 25      3,446      0.40Arkansas        1,472870,000   0.4049      790,041650,000            1,95937 
Calif.                                                                                                    
810,000                                                                                                   
San Juan,         4,585,000  19,960-38    2.32-4,980,000            7,141-16     1.94   3,832,664Colorado   752,3362,100,000 
P.R.            -11,750,000                                                                               
California                                                                                                
Santa Ana,     1,436,000 81      6,250   0.73Connecticut     2,939-1,360,000  0.80-36 1,577,398-1,410,000        -141,398-37 
Calif.                                                                                                    
1,700,000                                                                                                 
Sarasota,           397,000   1,730-40      0.20-220,000              792-12     0.22  425,076District of  -28,076-1,520,000 
Fla. Delaware      -740,000                                                                      Columbia 
Seattle,      1,688,000 -42      7,347       0.86Florida      3,2212,970,000   0.8810   1,728,751-110,000          -40,7510d 
Wash.                                                                                                     
-1,800,000                                                                                                
South             1,387,000   6,039-38    0.70-4,060,000            3,108-43     0.85     1,668,102Hawaii   -281,102-480,000 
Carolina         -3,530,000                                                                               
Georgia                                                                                                   
Springfield,    461,000 -14      2,005        0.23Idahoc          861-80,000  0.23-16     462,109-110,000          -1,109-23 
Mass.                                                                                                     
-170,000                                                                                                  
Tampa, Fla.       2,221,000   9,670-36       1.13-60,000             4,201-1     1.14    2,254,729Indiana   -33,7291,210,000 
Illinois         -3,200,000                                                                               
Tennessee        739,000 21      3,218          0.37Iowa         1,68930,000    0.463      906,507-40,000         -167,507-5 
810,000                                                                                                   
Texas Kansas      2,736,000   11,91121       1.39110,000             6,02411     1.64   3,233,156Kentucky   -497,156-940,000 
                    210,000                                                                               
Tucson, Ariz.   402,000 -45      1,749     0.20Louisiana        7802,110,000   0.2134    418,6361,380,000          -16,63622 
-1,060,000                                                                                                
Utah Mainec         120,000     524-42        0.0650,000               25710     0.07     137,935Maryland  -17,935-3,020,000 
                   -210,000                                                                               
Virginia         640,000 35      2,788 0.32Massachusetts     1,282-1,910,000  0.35-37      688,065530,000          -48,06510 
2,980,000                                                                                                 
Virginia          1,022,000    4,45027       0.52680,000             2,02416     0.55  1,086,306Minnesota     -64,306650,000 
Beach, Va.        1,180,000                                                                               
Michigan                                                                                                  
Wake County,     345,000 48      1,502   0.17Mississippi        8631,630,000   0.2349    463,1831,220,000         -118,18337 
N.C. 490,000                                                                                              
Warren, Mich.       405,000    1,76345       0.21880,000               70932     0.19     380,529Montanac     24,471-390,000 
Missouri          1,260,000                                                                               
Washington      652,000 -33      2,839      0.33Nebraska        1,357150,000   0.3724       728,31990,000          -76,31914 
-170,000                                                                                                  
West Palm         2,019,000    8,78950       1.02600,000             4,11236     1.12        2,206,962New   -187,962-310,000 
Beach, Fla.         840,000                                                                    Hampshirec 
Nevada                                                                                                    
Wilmington,     566,000 -24      2,459    0.29New Jersey      1,2782,140,000   0.3517      685,919760,000          -119,9196 
Del. -120,000                                                                                             
Wisconsin New       405,000     1,7615       0.21-50,000               795-4     0.22     426,686New York    -21,686-600,000 
Mexico               60,000                                                                               
Woodbridge,   1,462,000 -11      6,363         0.74North      2,3325,030,000   0.6368  1,251,6144,020,000          210,38654 
N.J.                                            Carolina                                                  
-4,640,000                                                                                                
Worcester,          369,000   1,607-62      0.19-130,000              768-65     0.21         412,195Ohio   -43,1952,420,000 
Mass. North        -120,000                                                                               
Dakotae                                                                                                   
Total          $197,288,000    858,752  367,5861,010,000 $197,288,000760,000 Oklahoma                  49                 37 
1,750,00                 32                                                                               

Sources: GAO analysis of CDC and HUD data. Oregon

Notes: By law HOPWA base grants are distributed according to cumulative
AIDS case counts. -620,000

aThe number of living AIDS cases was calculated by subtracting the number
of reported deaths among AIDS cases in a jurisdiction from the number of
reported cases. -37

bThis was calculated by subtracting the amount that would have been
received if living AIDS cases had been used from the amount that was
received using cumulative AIDS cases. A positive value indicates that the
jurisdiction received more funding using cumulative AIDS cases than it
would have received if living AIDS cases had been used. A negative value
indicates that the jurisdiction would have received more funding if living
AIDS cases had been used. -280,000

                                                 Percent changePercent change

                                                                           38

                                                                           99

                                                                          -35

                                                                          -40

                                                                           32

                                                                          -40

                                                                          -36

                                                                           64

                                                                          -79

                                                                          -63

                                                                           -1

                                                                           45

-17

Appendix VI: Total CARE Act Title I and Title II Funding by State and
Territory, Fiscal Year 2004

Pennsylvania

-2,320,000                    -22    -3,080,000              -29 
-2,950,000                    -36    -3,450,000              -42 
-440,000                      -40      -170,000              -15 
2,370,000                      35     1,620,000               24 
-290,000                      -58      -310,000              -62 
2,250,000                      36     1,550,000               25 
870,000                         5      -990,000               -5 
110,000                        10        10,000                1 
-370,000                      -74      -260,000              -52 
2,370,000                      40     1,620,000               27 
-1,170,000                    -37       170,000                5 
150,000                        21        80,000               11 
940,000                        51       710,000               39 
-90,000                       -46      -100,000              -51 
Notes: HRSA              aIn some   bRounded to  cState received  dPercent 
calculates a       jurisdictions,       nearest  a Title II base    change 
jurisdiction's      HIV cases are      $10,000.         award of      that 
ELCs by using        collected by                  $500,000, the rounds to 
data from CDC on    name while in               minimum it could zero, but 
the reported     others HIV cases               receive based on  does not 
AIDS case counts    are collected                  the number of     equal 
for the last 10     using a coded                    ELCs in the      zero 
years and          identifier. We                     state. The  percent. 
weighting those   used both name-                      estimated 
numbers to         and code-based                changes compare 
account for the   case counts for               this amount with 
likelihood of      this estimate.                 what the state 
death.           CDC only accepts                     would have 
                     name-based case                received if HIV 
                        counts as no                case counts and 
                          code-based                  ELCs had been 
                      system has yet                        used to 
                     met its quality                      determine 
                           criteria.                 funding and if 
                                                     there had been 
                                                   no hold-harmless 
                                                                and 
                                                      minimum-grant 
                                                        provisions. 
     Appendix XIII:                                  Change in ADAP 
     Estimated CARE                                 base funding if 
      Act ADAP Base                                CDC-accepted HIV 
    Funding Changes                                 case counts and 
    from Use of HIV                                  ELCs were used 
    Case Counts and                                   to distribute 
       ELCs without                                 funding without 
      Hold-harmless                                   hold-harmless 
     Appendix XIII:                                provision Change 
     Estimated CARE                                    in ADAP base 
      Act ADAP Base                                      funding if 
    Funding Changes                                CDC-accepted HIV 
    from Use of HIV                                 case counts and 
    Case Counts and                                  ELCs were used 
       ELCs without                                   to distribute 
      Hold-harmless                                 funding without 
                                                      hold-harmless 
                                                          provision 
    Grantee Grantee           Dollar       Percent           Dollar 
                       changebDollar changePercent    changebDollar 
                             changeb        change          changeb 
            Alabama       $5,190,000           74%       $3,970,000 
             Alaska          -50,000           -10          -90,000 
            Arizona        3,550,000            42        2,370,000 
           Arkansas        1,820,000            59        1,330,000 
         California      -32,150,000           -36      -12,590,000 
           Colorado        5,970,000           106        4,820,000 
        Connecticut       -4,060,000           -36       -4,240,000 
           Delaware       -1,150,000           -36         -250,000 
        District of       -4,970,000           -36       -5,850,000 
           Columbia                                                 
            Florida       10,400,000            13        1,390,000 
            Georgia       -8,500,000           -36      -10,010,000 
             Hawaii         -750,000           -36         -210,000 
              Idaho          310,000            68          240,000 
           Illinois       -9,240,000           -36         -250,000 
            Indiana        2,690,000            41        1,770,000 
               Iowa          140,000            10          -10,000 
             Kansas          650,000            32          390,000 
           Kentucky       -1,470,000           -36       -1,730,000 
          Louisiana        5,440,000            39        3,530,000 
              Maine         -300,000           -36          160,000 
           Maryland       -9,240,000           -36        7,700,000 
      Massachusetts       -5,270,000           -36        1,530,000 
           Michigan        3,150,000            29        1,740,000 
          Minnesota        1,910,000            63        1,420,000 
        Mississippi        3,410,000            60        2,490,000 
           Missouri        3,600,000            49        2,510,000 
            Montana         -110,000           -36          300,000 
           Nebraska          360,000            32          210,000 
             Nevada        2,400,000            51        1,700,000 
      New Hampshire         -270,000           -36          210,000 
         New Jersey        6,500,000            19        2,390,000 
         New Mexico          250,000            12           20,000 
           New York       -1,110,000            -1      -13,400,000 
     North Carolina       10,190,000            79        7,900,000 
       North Dakota           50,000            57           40,000 
               Ohio        5,520,000            51        3,890,000 

                                                                  Puerto Rico

                                                                 Rhode Island

                                                               South Carolina

                                                                South Dakotac

                                                                    Tennessee

                                                                        Texas

                                                                         Utah

                                                                     Vermontc

                                                                     Virginia

                                                                   Washington

                                                                West Virginia

                                                                    Wisconsin

                                                                     Wyominge

                   Sources: GAO analysis of CDC, HRSA, state, and local data.

      eState received a Title II base award of $200,000, the minimum it could
      receive based on the number of ELCs in the state. The estimated changes
      compare this amount with what the state would have received if HIV case
     counts and ELCs had been used to determine funding and if there had been
                               no hold-harmless and minimum-grant provisions.

    Change in ADAP base funding if HIV case counts from all grantees and ELCs
    were used to distribute funding without hold-harmless provisionaChange in
    ADAP base funding if HIV case counts from all grantees and ELCs were used
                       to distribute funding without hold-harmless provisiona

                                                 Percent changePercent change

                                                                          57%

                                                                          -19

                                                                           28

                                                                           43

                                                                          -14

                                                                           86

                                                                          -38

                                                                           -8

                                                                          -42

                                                                            2

                                                                          -42

                                                                          -10

                                                                           51

                                                                           -1

                                                                           27

                                                                           -1

                                                                           19

                                                                          -42

                                                                           26

                                                                           19

                                                                           30

                                                                           10

                                                                           16

                                                                           47

                                                                           43

                                                                           34

                                                                           95

                                                                           19

                                                                           36

                                                                           28

                                                                            7

                                                                            1

                                                                          -11

                                                                           62

                                                                           41

                                                                           36

Oklahoma

2,100,000

59

1,540,000

43

Table 13: EMAs with No Service Area Changes

                       HRSA 2004 EMA                         GAO-identified comparable OMB Changes  
                                                             newly defined 2004 MSA(s) or           
                                                                       MDIV(s)a                     
OMB's 1993 full title of metropolitan area     Number   ELCs OMB's 2004 full title of        Number   ELCs Decrease Increase Change in 
                                                   of     in metropolitan area(s)                of     in       in       in      ELCs 
                                             counties   EMAs                               counties   EMAs counties counties (percent) 
                                               in EMA                                        in EMA                          
Austin-San Marcos, Tex. MSA                         5  1,651 Austin-Round Rock, Tex. MSA          5  1,651        0        0        0% 
Baltimore, Md. PMSA                                 7  8,348 Baltimore-Towson, Md. MSA            7  8,348        0        0         0 
Fort Lauderdale, Fla. PMSA                          1  6,002 Fort Lauderdale-Pompano              1  6,002        0        0         0 
                                                             Beach-Deerfield Beach, Fla.                                     
                                                             MDIV                                                            
Hartford, Conn. NECMA                               3  1,954 Hartford-West Hartford-East          3  1,954        0        0         0 
                                                             Hartford, Conn. MSA                                             
Los Angeles-Long Beach, Calif. PMSA                 1 15,180 Los Angeles-Long                     1 15,180        0        0         0 
                                                             Beach-Glendale, Calif. MDIV                                     
Miami, Fla. PMSA                                    1 10,485 Miami-Miami Beach-Kendall,           1 10,485        0        0         0 
                                                             Fla. MDIV                                                       
Minneapolis-St. Paul, Minn.-Wis. MSA               13  1,272 Minneapolis-St.                     13  1,272        0        0         0 
                                                             Paul-Bloomington, Minn.-Wis.                                    
                                                             MSA                                                             
Nassau-Suffolk, N.Y. PMSA                           2  2,588 Nassau-Suffolk, N.Y. MDIV            2  2,588        0        0         0 
New                                                 2  2,945 Bridgeport-Stamford-Norwalk,         2  2,945        0        0         0 
Haven-Bridgeport-Stamford-Waterbury-Danbury,                 Conn. MSA and New                                               
Conn. NECMA                                                  Haven-Milford, Conn. MSA                                        
Oakland, Calif. PMSA                                2  2,852 Oakland-Fremont-Hayward,             2  2,852        0        0         0 
                                                             Calif. MDIV                                                     
Orange County, Calif. PMSA                          1  2,183 Santa Ana-Anaheim-Irvine,            1  2,183        0        0         0 
                                                             Calif. MDIV                                                     
Orlando, Fla. MSA                                   4  3,293 Orlando-Kissimmee, Fla. MSA          4  3,293        0        0         0 
Phoenix-Mesa, Ariz. MSA                             2  2,850 Phoenix-Mesa-Scottsdale,             2  2,850        0        0         0 
                                                             Ariz. MSA                                                       
Riverside-San Bernardino, Calif. PMSA               2  3,204 Riverside-San                        2  3,204        0        0         0 
                                                             Bernardino-Ontario, Calif.                                      
                                                             MSA                                                             
San Diego, Calif. MSA                               1  4,259 San Diego-Carlsbad San               1  4,259        0        0         0 
                                                             Marcos, CA MSA                                                  
San Francisco, Calif. PMSA                          3  7,216 San Francisco-San                    3  7,216        0        0         0 
                                                             Mateo-Redwood City, Calif.                                      
                                                             MDIV                                                            
Santa Rosa, Calif. PMSA                             1    482 Santa Rosa-Petaluma, Calif.          1    482        0        0         0 
                                                             MSA                                                             
Tampa-St. Petersburg-Clearwater, Fla. MSA           4  3,875 Tampa-St.                            4  3,875        0        0         0 
                                                             Petersburg-Clearwater, Fla.                                     
                                                             MSA                                                             
Vineland-Millville-Bridgeton, N.J. PMSA             1    388 Vineland-Millville-Bridgeton,        1    388        0        0         0 
                                                             N.J. MSA                                                        
West Palm Beach-Boca Raton, Fla. MSA                1  3,741 West Palm Beach-Boca                 1  3,741        0        0         0 
                                                             Raton-Boynton Beach, Fla.                                       
                                                             MDIV                                                            
Total                                              57 84,768 Not applicable                      57 84,768        0        0         0 

     HIV/AIDS FundingHIV/AIDS FundingHIV/AIDS FundingHIV/AIDS FundingHIV/AIDS
              FundingHIV/AIDS FundingHIV/AIDS FundingHIV/AIDS FundingHIV/AIDS
              FundingHIV/AIDS FundingHIV/AIDS FundingHIV/AIDS FundingHIV/AIDS
                                      FundingHIV/AIDS FundingHIV/AIDS Funding

Sources: GAO analysis of CDC, HRSA, and OMB data.

Notes: This table uses OMB's terminology for classifying types of
metropolitan areas. Specifically, it includes metropolitan statistical
area (MSA), primary metropolitan statistical area (PMSA), New England
county metropolitan area (NECMA), and metropolitan division (MDIV). The
terms used and meaning of those terms differs between1993 and 2004 because
of OMB's fundamental revisions of metropolitan concepts. For further
explanation, see GAO-04-758 .

aWe chose whatever combination of the newly defined metropolitan areas
that would result in the least change to the numbers of ELCs within the
EMA's boundaries.

Oregon

-1,520,000

                      -36                          -600,000       -14    
Pennsylvania -6,540,000        -24 -8,540,000              -32    Puerto Rico     -7,890,000      -35   
-41               Rhode -690,000             -36      -210,000            -11        South Carolina     
                 Island                                                                                 
44            3,510,000         30  South Dakota       180,000             90        150,000       71   
Tennessee     4,880,000         46 3,330,000                31          Texas      3,440,000        7   
-4                 Utah 330,000               18       110,000              6               Vermont     
-36              50,000         14      Virginia     6,260,000             43      4,200,000       29   
Washington   -2,860,000        -36 720,000                   9  West Virginia        380,000       29   
16            Wisconsin 1,950,000             61     1,440,000             45               Wyoming     
24               20,000         12  Sources: GAO    Notes: The           HRSA       aIn some bRounded   
                                     analysis of     ADAP base   calculates a jurisdictions,       to   
                                      CDC, HRSA, grant funding jurisdiction's  HIV cases are  nearest   
                                      state, and        levels  ELCs by using   collected by $10,000.   
                                     local data.   reported to  data from CDC  name while in            
                                                   us included         on the     others HIV            
                                                           any  reported AIDS      cases are            
                                                 hold-harmless    case counts      collected            
                                                  funding that   for the last  using a coded            
                                                         would   10 years and identifier. We            
                                                  otherwise be      weighting      used both            
                                                 used for ADAP  those numbers      name- and            
                                                   Severe Need to account for     code-based            
                                                   grants. The the likelihood    case counts            
                                                     estimated      of death.       for this            
                                                    dollar and                 estimate. CDC            
                                                       percent                  only accepts            
                                                       changes                    name-based            
                                                     presented                case counts as            
                                                      here are                 no code-based            
                                                 based on what                system has yet            
                                                      grantees                       met its            
                                                   received in                       quality            
                                                    their ADAP                     criteria.            
                                                   base grants                                          
                                                  without this                                          
                                                 hold-harmless                                          
                                                      funding.                                          
Appendix                           Change in         Change in        Grantee Dollar changeb  Percent   
XIV:                               HOPWA base       HOPWA base                                 change   
Estimated                          funding if   funding if HIV                                          
HOPWA Base                         CDC-accepted    case counts                                          
Funding                            HIV case           from all                                          
Changes from                       counts and     grantees and                                          
Use of HIV                         living AIDS     living AIDS                                          
and Living                         case counts     case counts                                          
AIDS Case                          were used to   were used to                                          
Counts,                            distribute       distribute                                          
Fiscal Year                        funding            fundinga                                          
2004                                                                                                    
Appendix                                                                                                
XIV:                                                                                                    
Estimated                                                                                               
HOPWA Base                                                                                              
Funding                                                                                                 
Changes from                                                                                            
Use of HIV                                                                                              
and Living                                                                                              
AIDS Case                                                                                               
Counts,                                                                                                 
Fiscal Year                                                                                             
2004                                                                                                    
Percent         Alabama $1,150,000          101%      $960,000            84%          Albany, N.Y.     
change                                                                                                  
18               30,000          8       Arizona        60,000             39         40,000       27   
Arkansas        630,000         84 520,000                  69   Atlanta, Ga.     -1,160,000      -27   
-33            Augusta, 10,000                 3       -20,000             -6          Austin, Tex.     
                    Ga.                                                                                 
7               -20,000         -2    Baltimore,    -1,170,000            -30      1,770,000       45   
                                             Md.                                                        
Baton Rouge,    470,000         71 370,000                  56    Birmingham,        550,000      106   
La.                                                                      Ala.                           
89              Boston, -650,000             -36       110,000              6     Bridgeport, Conn.     
                  Mass.                                                                                 
-21            -180,000        -24 Buffalo, N.Y.        30,000              6        -10,000       -3   
California   -1,150,000        -38 -600,000                -20     Cambridge,       -200,000      -30   
                                                                        Mass.                           
16              Camden, 180,000               27       110,000             16      Charleston, S.C.     
                   N.J.                                                                                 
72              230,000         57    Charlotte,       900,000            158        780,000      137   
                                            N.C.                                                        
Chicago,     -1,860,000        -33 -10,000                  0c    Cincinnati,        200,000       36   
Ill.                                                                     Ohio                           
24           Cleveland, 410,000               48       300,000             35              Colorado     
                   Ohio                                                                                 
97              290,000         80     Columbia,       600,000             96        490,000       80   
                                            S.C.                                                        
Columbus,       360,000         61 280,000                  48    Connecticut        -60,000      -24   
Ohio                                                                                                    
-28             Dallas, 590,000               19       270,000              9              Delaware     
                   Tex.                                                                                 
-22              30,000         18 Denver, Colo.     1,210,000             85        990,000       69   
Detroit,        270,000         17 110,000                   7    District of       -230,000       -4   
Mich.                                                                Columbia                           
0c              Florida -660,000             -16      -950,000            -23           Fort            
                                                                                 Lauderdale,            
                                                                                        Fla.            
24              460,000         14   Fort Worth,       110,000             13         30,000          3 
                                            Tex.                                                        

                                                                   -9,350,000

                                                                    5,190,000

                                                                   -1,920,000

                                                                     -140,000

                                                                      210,000

                                                                       40,000

                                                               Dollar changeb

                                                                       80,000

                                                                   -1,420,000

                                                                       70,000

                                                                      460,000

                                                                     -160,000

                                                                      110,000

                                                                      290,000

                                                                      130,000

                                                                      350,000

                                                                      -70,000

                                                                      -40,000

                                                                       20,000

                                                                      820,000

Appendix VIII: Estimated CARE Act Title I Funding Changes from Use of HIV
Case Counts and ELCs with Hold-harmless Appendix VIII: Estimated CARE Act
Title I Funding Changes from Use of HIV Case Counts and ELCs with
Hold-harmless

                                 Change in Title I  Change in Title I 
                                  base funding if    base funding if  
                                  CDC-accepted HIV   HIV case counts  
                                  case counts and   from all grantees 
                                 ELCs were used to    and ELCs were   
                                 distribute funding      used to      
                                 with hold-harmless    distribute     
                                     provision        funding with    
                                                      hold-harmless   
                                                       provisiona     
Eligible metropolitan area        Dollar Percent    Dollar changeb Percent 
                                    changeb  change                    change 
Atlanta, Ga.                   -$210,000     -2%         -$210,000     -2% 
Austin, Tex.                     260,000      13           -10,000      0c 
Baltimore, Md.                  -240,000      -2         3,210,000      32 
Bergen-Passaic, N.J.             600,000      23           210,000       8 
Boston, Mass.                          0       0         1,180,000      16 
Caguas, P.R.                     -50,000      -5           -50,000      -5 
Chicago, Ill.                   -950,000      -7           510,000       4 
Cleveland, Ohio                  940,000      51           610,000      33 
Dallas, Tex.                   1,630,000      25           660,000      10 
Denver, Colo.                  3,210,000     132         2,530,000     104 
Detroit, Mich.                 1,520,000      35           810,000      19 
District of Columbia            -750,000      -5          -750,000      -5 
Dutchess County, N.Y.             40,000       7           -30,000      -5 
Fort Lauderdale, Fla.          2,060,000      28           940,000      13 
Fort Worth, Tex.                 350,000      19            90,000       5 
Hartford, Conn.                  -80,000      -3           -80,000      -3 
Houston, Tex.                  1,130,000      12           -20,000      0c 
Jacksonville, Fla.               570,000      23           200,000       8 
Jersey City, N.J.                590,000      20           160,000       5 
Kansas City, Mo.                 870,000      51           560,000      32 
Las Vegas, Nev.                1,460,000      61         1,000,000      42 
Los Angeles, Calif.              -10,000      0c           -10,000      0c 
Miami, Fla.                    3,580,000      28         1,620,000      13 
Middlesex-Somerset-Hunterdon,    400,000      26           170,000      11 
N.J.                                                               
Minneapolis-St. Paul, Minn.    1,130,000      71           810,000      51 
Nassau-Suffolk, N.Y.              40,000       1            40,000       1 
New Haven, Conn.                       0       0                 0       0 
New Orleans, La.               1,950,000      51         1,250,000      33 
New York, N.Y.                 5,660,000       9          -310,000      -1 
Newark, N.J.                   2,360,000      29         1,100,000      14 
Norfolk, Va.                   1,560,000      57         1,040,000      38 
Oakland, Calif.                        0       0                 0       0 
Orange County, Calif.            -30,000      -1           -30,000      -1 
Orlando, Fla.                  1,190,000      30           570,000      14 
Philadelphia, Pa.               -230,000      -2          -230,000      -2 
Phoenix, Ariz.                 2,020,000      58         1,360,000      39 
Ponce, P.R.                      -30,000      -2           -30,000      -2 
Portland, Oreg.                  -20,000      -1           -20,000      -1 
Riverside-San Bernardino,        -90,000      -2           -90,000      -2 
Calif.                                                             
Sacramento, Calif.                     0       0                 0       0 
St. Louis, Mo.                 1,120,000      47           830,000      34 
San Antonio, Tex.                180,000       8           -20,000      -1 
San Diego, Calif.               -120,000      -2           800,000      15 
San Francisco, Calif.                  0       0                 0       0 
San Jose, Calif.                       0       0                 0       0 
San Juan, P.R.                         0       0                 0       0 
Santa Rosa, Calif.                     0       0                 0       0 
Seattle, Wash.                         0       0           640,000      21 
Tampa-St. Petersburg, Fla.     1,000,000      21           310,000       7 
Vineland-Millville-Bridgeton,    130,000      28            60,000      12 
N.J.                                                               
West Palm Beach, Fla.            530,000      12                 0       0 

Sources: GAO analysis of CDC, HRSA, state, and local data.

Notes: The estimated dollar and percent changes are based on what the EMAs
received in their base grants, including any hold-harmless funding, and
what they would have received if HIV cases and ELCs had been used to
allocate funding. In fiscal year 2004, the amount of hold-harmless funding
was $8,033,563. Because the amounts needed to fund the Title I
hold-harmless provision are taken from funds that would otherwise be
available for supplemental grants, the total funding actually allocated as
base grants and our estimated base grant funding differ by the amounts
necessary to fund the hold-harmless provision. The hold-harmless funding
was $43,300,968 when only CDC-accepted HIV case counts and ELCs were used
and $29,413,708 when the HIV case counts from all grantees were used.

HRSA calculates a jurisdiction's ELCs by using data from CDC on the
reported AIDS case counts for the last 10 years and weighting those
numbers to account for the likelihood of death.

aIn some jurisdictions, HIV cases are collected by name while in others
HIV cases are collected using a coded identifier. We used both name- and
code-based case counts for this estimate. CDC only accepts name-based case
counts as no code-based system has yet met its quality criteria.

bRounded to nearest $10,000.

cPercent change that rounds to zero, but does not equal zero percent.

Appendix IX: Estimated CARE Act Title II Base Funding Changes from Use of
HIV Case Counts and ELCs with Hold-harmless Appendix IX: Estimated CARE
Act Title II Base Funding Changes from Use of HIV Case Counts and ELCs
with Hold-harmless

                    Change in Title II base   Change in Title II base 
                  funding if CDC-accepted HIV   funding if HIV case   
                   case counts and ELCs were      counts from all     
                  used to distribute funding  grantees and ELCs were  
                    with hold-harmless and      used to distribute    
                   minimum-grant provisions        funding with       
                                                 hold-harmless and    
                                                   minimum-grant      
                                                    provisionsa       
Grantee           Dollar changeb   Percent          Dollar changeb Percent 
                                       change                          change 
Alabama               $1,170,000       29%              $1,000,000     25% 
Alaskac                        0         0                       0       0 
Arizona                  620,000        19                 410,000      13 
Arkansas                 320,000        18                 250,000      14 
California                     0         0                       0       0 
Colorado               1,540,000        73               1,340,000      63 
Connecticut             -150,000        -4                -150,000      -4 
Delaware                -410,000       -22                -410,000     -22 
District of             -940,000       -22                -940,000     -22 
Columbia                                                           
Florida               -1,330,000        -4              -2,910,000     -10 
Georgia               -1,350,000       -14              -1,350,000     -14 
Hawaii                   -70,000        -6                 -70,000      -6 
Idahoc                         0         0                       0       0 
Illinois              -1,780,000       -20                -780,000      -9 
Indiana                  180,000         5                  50,000       1 
Iowa                     -90,000       -11                 -90,000     -11 
Kansas                         0         0                       0       0 
Kentucky                -400,000       -17                -400,000     -17 
Louisiana                700,000        11                 390,000       6 
Mainec                         0         0                       0       0 
Maryland              -1,650,000       -20               2,060,000      24 
Massachusetts           -620,000       -12                  20,000      0d 
Michigan                 370,000         9                 130,000       3 
Minnesota                460,000        45                 370,000      36 
Mississippi              590,000        18                 460,000      14 
Missouri                 720,000        26                 520,000      19 
Montanac                       0         0                       0       0 
Nebraska                 -10,000        -2                 -30,000      -5 
Nevada                   520,000        31                 400,000      24 
New Hampshirec                 0         0                       0       0 
New Jersey               370,000         3                       0       0 
New Mexico               -70,000        -6                 -70,000      -6 
New York              -1,730,000        -4              -1,730,000      -4 
North Carolina         2,440,000        33               2,120,000      29 
North Dakotae            300,000       150                 300,000     150 
Ohio                     940,000        17                 690,000      13 
Oklahoma                 370,000        18                 290,000      14 
Oregon                  -130,000        -8                -130,000      -8 
Pennsylvania          -1,840,000       -17              -1,840,000     -17 
Puerto Rico             -320,000        -4                -320,000      -4 
Rhode Island             -30,000        -2                 -30,000      -2 
South Carolina           470,000         7                 230,000       3 
South Dakotac                  0         0                       0       0 
Tennessee                490,000         8                 270,000       4 
Texas                 -1,140,000        -6              -1,140,000      -6 
Utah                     -60,000        -6                 -60,000      -6 
Vermontc                       0         0                       0       0 
Virginia               1,100,000        19                 750,000      13 
Washington              -200,000        -7                -170,000      -5 
West Virginia            -20,000        -3                 -50,000      -7 
Wisconsin                360,000        20                 290,000      16 
Wyominge                 300,000       150                 300,000     150 

Sources: GAO analysis of CDC, HRSA, state, and local data.

Notes: HRSA calculates a jurisdiction's ELCs by using data from CDC on the
reported AIDS case counts for the last 10 years and weighting those
numbers to account for the likelihood of death.

For purposes of this analysis, we considered the Title II hold-harmless
provision that is funded by proportional reductions in Title II base
grants. We did not include the Title II hold-harmless provision funded by
amounts otherwise available for Severe Need grants.

aIn some jurisdictions, HIV cases are collected by name while in others
HIV cases are collected using a coded identifier. We used both name- and
code-based case counts for this estimate. CDC only accepts name-based case
counts as no code-based system has yet met its quality criteria.

bRounded to nearest $10,000.

cState received a Title II base award of $500,000, the minimum it could
receive based on the number of AIDS cases in the state.

dPercent change that rounds to zero, but does not equal zero percent.

eState received a Title II base award of $200,000, the minimum it could
receive based on the number of AIDS cases in the state.

Appendix X: Estimated CARE Act ADAP Base Funding Changes from Use of HIV
Case Counts and ELCs with Hold-harmless Appendix X: Estimated CARE Act
ADAP Base Funding Changes from Use of HIV Case Counts and ELCs with
Hold-harmless

                     Change in ADAP base       Change in ADAP base   
                   funding if CDC-accepted     funding if HIV case   
                   HIV case counts and ELCs      counts from all     
                   were used to distribute   grantees and ELCs were  
                  funding with hold-harmless   used to distribute    
                          provision               funding with       
                                                  hold-harmless      
                                                   provisiona        
Grantee          Dollar changeb   Percent           Dollar changeb Percent 
                                      change                           change 
Alabama              $4,810,000       69%              $3,860,000      55%
Alaska                  -60,000       -13                 -90,000      -20
Arizona               3,180,000        38               2,260,000       27
Arkansas              1,670,000        54               1,290,000       42
California          -18,530,000       -21             -13,400,000      -15
Colorado              5,610,000       100               4,710,000       84
Connecticut          -2,970,000       -26              -2,970,000      -26
Delaware             -1,210,000       -38                -280,000       -9
District of          -5,240,000       -38              -5,490,000      -40
Columbia                                                          
Florida               7,570,000         9                 530,000        1
Georgia              -8,120,000       -34              -8,120,000      -34
Hawaii                 -610,000       -30                -230,000      -11
Idaho                   290,000        62                 230,000       49
Illinois             -9,750,000       -38                -520,000       -2
Indiana               2,400,000        37               1,690,000       26
Iowa                     90,000         7                 -20,000       -2
Kansas                  570,000        28                 360,000       18
Kentucky             -1,550,000       -38              -1,550,000      -38
Louisiana             4,840,000        35               3,350,000       24
Maine                  -260,000       -32                 150,000       18
Maryland             -9,750,000       -38               7,340,000       29
Massachusetts        -4,760,000       -32               1,360,000        9
Michigan              2,710,000        25               1,610,000       15
Minnesota             1,750,000        58               1,370,000       46
Mississippi           3,120,000        54               2,410,000       42
Missouri              3,260,000        44               2,400,000       32
Montana                 -80,000       -25                 290,000       93
Nebraska                310,000        28                 200,000       18
Nevada                2,180,000        46               1,630,000       34
New Hampshire          -170,000       -22                 200,000       26
New Jersey            5,210,000        15               2,000,000        6
New Mexico              170,000         8                 -10,000       0c
New York             -4,960,000        -4             -14,570,000      -12
North Carolina        9,470,000        74               7,680,000       60
North Dakota             50,000        52                  40,000       40
Ohio                  5,010,000        46               3,730,000       34
Oklahoma              1,930,000        54               1,490,000       42
Oregon               -1,230,000       -29                -640,000      -15
Pennsylvania         -7,180,000       -27              -8,780,000      -32
Puerto Rico          -5,900,000       -26              -5,900,000      -26
Rhode Island           -520,000       -27                -230,000      -12
South Carolina        4,660,000        40               3,350,000       29
South Dakota            170,000        84                 140,000       69
Tennessee             4,400,000        41               3,180,000       30
Texas                 1,760,000         4              -2,430,000       -5
Utah                    260,000        14                  90,000        5
Vermont                -130,000       -35                  50,000       12
Virginia              5,610,000        39               4,000,000       28
Washington           -2,220,000       -28                 630,000        8
West Virginia           330,000        25                 200,000       15
Wisconsin             1,790,000        56               1,400,000       44
Wyoming                  30,000        20                  20,000       11

Sources: GAO analysis of CDC, HRSA, state, and local data.

Notes: The ADAP base grant funding levels reported to us included any
hold-harmless funding that would otherwise be used for ADAP Severe Need
grants. The estimated dollar and percent changes presented here are based
on what grantees received in their ADAP base grants without this
hold-harmless funding.

HRSA calculates a jurisdiction's ELCs by using data from CDC on the
reported AIDS case counts for the last 10 years and weighting those
numbers to account for the likelihood of death.

For purposes of this analysis, we considered the Title II hold-harmless
provision that is funded by proportional reductions in ADAP base grants.
We did not include the Title II hold-harmless provision funded by amounts
otherwise available for Severe Need grants.

aIn some jurisdictions, HIV cases are collected by name while in others
HIV cases are collected using a coded identifier. We used both name- and
code-based case counts for this estimate. CDC only accepts name-based case
counts as no code-based system has yet met its quality criteria.

bRounded to nearest $10,000.

cPercent change that rounds to zero, but does not equal zero percent.

Appendix XI: Estimated CARE Act Title I Base Funding Changes from Use of
HIV Case Counts and ELCs without Hold-harmless Appendix XI: Estimated CARE
Act Title I Base Funding Changes from Use of HIV Case Counts and ELCs
without Hold-harmless

                                   Change in Title I     Change in    
                                    base funding if     Title I base  
                                 CDC-accepted HIV case funding if HIV 
                                 counts and ELCs were   case counts   
                                  used to distribute      from all    
                                    funding without     grantees and  
                                     hold-harmless     ELCs were used 
                                       provision       to distribute  
                                                          funding     
                                                          without     
                                                       hold-harmless  
                                                         provisiona   
Eligible metropolitan area          Dollar  Percent Dollar changeb Percent 
                                      changeb   change                 change 
Atlanta, Ga.                   -$2,830,000     -31%    -$3,600,000    -39% 
Austin, Tex.                       260,000       13        -10,000      0c 
Baltimore, Md.                  -3,110,000      -31      3,210,000      32 
Bergen-Passaic, N.J.               600,000       23        210,000       8 
Boston, Mass.                   -2,310,000      -31      1,180,000      16 
Caguas, P.R.                      -260,000      -28       -340,000     -37 
Chicago, Ill.                   -3,900,000      -31        510,000       4 
Cleveland, Ohio                    940,000       51        610,000      33 
Dallas, Tex.                     1,630,000       25        660,000      10 
Denver, Colo.                    3,210,000      132      2,530,000     104 
Detroit, Mich.                   1,520,000       35        810,000      19 
District of Columbia            -2,330,000      -16     -1,390,000     -10 
Dutchess County, N.Y.               40,000        7        -40,000      -6 
Fort Lauderdale, Fla.            2,060,000       28        940,000      13 
Fort Worth, Tex.                   350,000       19         90,000       5 
Hartford, Conn.                   -730,000      -31       -800,000     -34 
Houston, Tex.                    1,130,000       12       -140,000      -1 
Jacksonville, Fla.                 570,000       23        200,000       8 
Jersey City, N.J.                  590,000       20        160,000       5 
Kansas City, Mo.                   870,000       51        560,000      32 
Las Vegas, Nev.                  1,460,000       61      1,000,000      42 
Los Angeles, Calif.             -5,660,000      -31     -2,660,000     -14 
Miami, Fla.                      3,580,000       28      1,620,000      13 
Middlesex-Somerset-Hunterdon,      400,000       26        170,000      11 
N.J.                                                               
Minneapolis-St. Paul, Minn.      1,130,000       71        810,000      51 
Nassau-Suffolk, N.Y.              -940,000      -29     -1,210,000     -38 
New Haven, Conn.                -1,140,000      -31     -1,270,000     -35 
New Orleans, La.                 1,950,000       51      1,250,000      33 
New York, N.Y.                   5,660,000        9     -2,240,000      -4 
Newark, N.J.                     2,360,000       29      1,100,000      14 
Norfolk, Va.                     1,560,000       57      1,040,000      38 
Oakland, Calif.                 -1,100,000      -32       -680,000     -19 
Orange County, Calif.             -810,000      -31       -190,000      -7 
Orlando, Fla.                    1,190,000       30        570,000      14 
Philadelphia, Pa.               -2,620,000      -22     -3,750,000     -31 
Phoenix, Ariz.                   2,020,000       58      1,360,000      39 
Ponce, P.R.                       -420,000      -29       -540,000     -38 
Portland, Oreg.                   -580,000      -31        -90,000      -5 
Riverside-San Bernardino,       -1,190,000      -31       -170,000      -4 
Calif.                                                             
Sacramento, Calif.                -500,000      -32       -330,000     -21 
St. Louis, Mo.                   1,120,000       47        830,000      34 
San Antonio, Tex.                  180,000        8       -100,000      -5 
San Diego, Calif.               -1,590,000      -31        800,000      15 
San Francisco, Calif.          -10,050,000      -62     -8,470,000     -52 
San Jose, Calif.                  -440,000      -31        -30,000      -2 
San Juan, P.R.                  -2,430,000      -30     -3,120,000     -38 
Santa Rosa, Calif.                -200,000      -33        -30,000      -5 
Seattle, Wash.                    -930,000      -31        640,000      21 
Tampa-St. Petersburg, Fla.       1,000,000       21        310,000       7 
Vineland-Millville-Bridgeton,      130,000       28         60,000      12 
N.J.                                                               
West Palm Beach, Fla.              530,000       12        -80,000      -2 

Sources: GAO analysis of CDC, HRSA, state, and local data.

Notes: The estimated dollar and percent changes are based on what the EMAs
actually received in their base grants, which includes hold-harmless
funding, and what they would have received using HIV cases and ELCs if
there had been no hold-harmless provision. Because hold-harmless funding
is taken from amounts otherwise available for supplemental grants, the
total funding actually allocated as base grants and our estimated funding
differ by the amount of the hold-harmless funding ($8,033,563).

HRSA calculates a jurisdiction's ELCs by using data from CDC on the
reported AIDS case counts for the last 10 years and weighting those
numbers to account for the likelihood of death.

aIn some jurisdictions, HIV cases are collected by name while in others
HIV cases are collected using a coded identifier. We used both name- and
code-based case counts for this estimate. CDC only accepts name-based case
counts as no code-based system has yet met its quality criteria.

bRounded to nearest $10,000.

cPercent change that rounds to zero, but does not equal zero percent.

Appendix XII: Estimated CARE Act Title II Base Funding Changes from Use of
HIV Case Counts and ELCs without Hold-harmless

                               Change in HOPWA base      Change in    
                             funding if CDC-accepted     HOPWA base   
                            HIV case counts and living funding if HIV 
                            AIDS case counts were used  case counts   
                              to distribute funding       from all    
                                                        grantees and  
                                                        living AIDS   
                                                        case counts   
                                                        were used to  
                                                         distribute   
                                                          fundinga    
Grantee                     Dollar changeb  Percent Dollar changeb Percent 
                                                change                 change 
Gaithersburg, Md.                 -120,000      -22        190,000      35 
Georgia                           -340,000      -23       -440,000     -29 
Hartford, Conn.                   -220,000      -21       -230,000     -23 
Hawaii                             -30,000      -17         10,000       5 
Honolulu, Hawaii                  -160,000      -37        -70,000     -16 
Houston, Tex.                     -260,000       -5       -660,000     -13 
Illinois                          -190,000      -22        140,000      17 
Indiana                            470,000       56        360,000      43 
Indianapolis, Ind.                 420,000       56        320,000      42 
Iowa                                60,000       17         30,000       8 
Islip, N.Y.                       -300,000      -18       -410,000     -25 
Jackson, Miss.                     450,000       99        370,000      82 
Jacksonville, Fla.                 290,000       24        160,000      14 
Kansas                              90,000       25         50,000      15 
Kentucky                           -60,000      -13        -90,000     -21 
Kansas City, Mo.                   360,000       36        240,000      25 
Las Vegas, Nev.                    710,000       77        570,000      62 
Los Angeles, Calif.             -4,370,000      -42     -3,660,000     -35 
Louisiana                          580,000       62        460,000      49 
Louisville, Ky.                    -40,000       -9        -80,000     -17 
Maryland                           -70,000      -20        710,000     204 
Massachusetts                     -160,000      -30         60,000      12 
Memphis, Tenn.                     940,000      102        780,000      85 
Miami, Fla.                      1,140,000       19        520,000       9 
Michigan                           370,000       41        270,000      29 
Milwaukee, Wis.                    340,000       66        260,000      52 
Minneapolis, Minn.                 350,000       42        250,000      30 
Minnesota                           60,000       56         50,000      43 
Mississippi                        630,000       84        520,000      68 
Missouri                           270,000       55        210,000      42 
Nashville, Tenn.                   680,000       93        560,000      77 
Nevada                             130,000       55        100,000      41 
New Haven, Conn.                  -200,000      -21       -220,000     -24 
HIV/AIDS FundingNew               -770,000      -70       -800,000     -72 
Jersey HIV/AIDS                                                    
FundingHIV/AIDS                                                    
FundingHIV/AIDS                                                    
FundingHIV/AIDS                                                    
FundingHIV/AIDS                                                    
FundingHIV/AIDS                                                    
FundingHIV/AIDS                                                    
FundingHIV/AIDS                                                    
FundingHIV/AIDS                                                    
FundingHIV/AIDS                                                    
FundingHIV/AIDS                                                    
FundingHIV/AIDS                                                    
FundingHIV/AIDS                                                    
FundingHIV/AIDS                                                    
FundingHIV/AIDS                                                    
FundingHIV/AIDS Funding                                            
New Mexico                         110,000       21         60,000      11 
New Orleans, La.                   760,000       43        550,000      31 
New York                           300,000       17        130,000       7 
New York, N.Y.                  -3,040,000       -9     -5,610,000     -17 
Newark, N.J.                        40,000        1       -330,000      -8 
North Carolina                   2,130,000      103      1,780,000      85 
Oakland, Calif.                   -780,000      -39       -670,000     -33 
Ohio                               500,000       49        370,000      36 
Oklahoma                           430,000       83        350,000      67 
Oklahoma City, Okla.               180,000       39        130,000      27 
Orlando, Fla.                      610,000       37        420,000      25 
Pennsylvania                       -50,000       -4       -180,000     -12 
Philadelphia, Pa.                 -730,000      -17     -1,040,000     -24 
Phoenix, Ariz.                     920,000       65        730,000      51 
Pittsburgh, Pa.                   -120,000      -19       -160,000     -26 
Portland, Oreg.                   -300,000      -30       -110,000     -11 
Poughkeepsie, N.Y.                 -30,000       -5        -80,000     -13 
Providence, R.I.                  -220,000      -27         40,000       5 
Puerto Rico                     -1,080,000      -62     -1,130,000     -65 
Richmond, Va.                      490,000       71        390,000      57 
Riverside, Calif.                 -380,000      -22        -90,000      -5 
Rochester, N.Y.                    170,000       29        110,000      18 
Sacramento, Calif.                -310,000      -37       -280,000     -33 
St. Louis, Mo.                     450,000       37        370,000      30 
Salt Lake City, Utah               120,000       32         80,000      21 
San Antonio, Tex.                  100,000       10            0 d       1 
San Diego, Calif.                 -820,000      -31         20,000       1 
San Francisco, Calif.           -3,950,000      -59     -3,420,000     -51 
San Jose, Calif.                  -260,000      -33       -100,000     -13 
San Juan, P.R.                  -1,990,000      -44     -2,210,000     -48 
Santa Ana, Calif.                 -370,000      -26       -130,000      -9 
Sarasota, Fla.                      40,000       11         10,000       1 
Seattle, Wash.                    -520,000      -31        170,000      10 
South Carolina                   1,040,000       75        840,000      61 
Springfield, Mass.                -150,000      -32         90,000      20 
Tampa, Fla.                        330,000       15        110,000       5 
Tennessee                          490,000       67        390,000      53 
Texas                              780,000       29        480,000      18 
Tucson, Ariz.                      210,000       53        160,000      40 
Utah                                30,000       26         20,000      15 
Virginia                           320,000       50        240,000      37 
Virginia Beach, Va.                720,000       71        580,000      56 
Wake County, N.C.                  360,000      105        300,000      88 
Warren, Mich.                      120,000       31         80,000      20 
Washington                        -160,000      -25         70,000      10 
West Palm Beach, Fla.              270,000       14         80,000       4 
Wilmington, Del.                   -70,000      -13        110,000      19 
Wisconsin                          220,000       54        170,000      41 
Woodbridge, N.J.                    50,000        4        -80,000      -5 
Worcester, Mass.                   -90,000      -25         80,000      22 

Sources: GAO analysis of CDC, HUD, state, and local data.

Notes: The number of living AIDS cases was calculated by subtracting the
number of reported deaths among AIDS cases in a jurisdiction from the
number of reported cases.

aIn some jurisdictions, HIV cases are collected by name while in others
HIV cases are collected using a coded identifier. We used both name- and
code-based case counts for this estimate. CDC only accepts name-based case
counts as no code-based system has yet met its quality criteria.

bRounded to nearest $10,000.

cPercent change that rounds to zero, but does not equal zero.

dDollar change that rounds to zero, but does not equal zero.

Appendix XV: Comments from the Department of Health and Human Services
Appendix XV: Comments from the Department of Health and Human Services

Appendix XVI: Comments from the Department of Housing and Urban
Development Appendix XVI: Comments from the Department of Housing and
Urban Development

Appendix XVII: GAO Contact and Staff Acknowledgments

GAO Contact

Marcia Crosse, (202) 512-7119 or [email protected]

Acknowledgments

In addition to the contact above, James McClyde, Assistant Director;
Robert Copeland; Robert Dinkelmeyer; Louise Duhamel; Cathy Hamann; Opal
Winebrenner; Craig Winslow; and Suzanne Worth made key contributions to
this report.

Related GAO Products Related GAO Products

Ryan White CARE Act: Factors that Impact HIV and AIDS Funding and Client
Coverage. GAO-05-841T . Washington, D.C.: June 23, 2005.

Ryan White CARE Act: Title I Funding for San Francisco. GAO/HEHS-00-189R .
Washington, D.C.: August 24, 2000.

Ryan White CARE Act: Opportunities to Enhance Funding Equity.
GAO/T-HEHS-00-150 . Washington, D.C.: July 11, 2000.

HIV/AIDS: Use of Ryan White CARE Act and Other Assistance Grant Funds.
GAO/HEHS-00-54 .Washington, D.C.: March 1, 2000.

HIV/AIDS Drugs: Funding Implications of New Combination Therapies for
Federal and State Programs. GAO/HEHS-99-2 .Washington, D.C.: October 14,
1998.

Revising Ryan White Funding Formulas. GAO/HEHS-96-116R . Washington, D.C.:
March 26, 1996.

Ryan White CARE Act of 1990: Opportunities to Enhance Funding Equity.
GAO/HEHS-96-26 . Washington, D.C.: November 13, 1995.

Ryan White CARE Act: Access to Services by Minorities, Women, and
Substance Abusers. GAO/T-HEHS-95-212 . Washington, D.C.: July 17, 1995.

Ryan White CARE Act of 1990: Opportunities Are Available to Improve
Funding Equity. GAO/T-HEHS-95-126 . Washington, D.C.: April 5, 1995.

Follow-up on Ryan White Testimony. GAO/HEHS-95-119R . Washington, D.C.:
March 31, 1995.

Ryan White CARE Act of 1990: Opportunities Are Available to Improve
Funding Equity. GAO/T-HEHS-95-91 . Washington, D.C.: February 22, 1995.

Ryan White Funding Formulas. GAO/HEHS-95-79R . Washington, D.C.: February
14, 1995.

Ryan White CARE Act: Access to Services by Minorities, Women, and
Substance Abusers. GAO/HEHS-95-49 . Washington, D.C.: January 13, 1995.

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Highlights of GAO-06-332 , a report to congressional requesters

February 2006

HIV/AIDS

Changes Needed to Improve the Distribution of Ryan White CARE Act and
Housing Funds

Among federal efforts to address the HIV/AIDS epidemic are the CARE Act of
1990 and the Housing Opportunities for Persons with AIDS program (HOPWA)
administered by the Departments of Health and Human Services (HHS) and
Housing and Urban Development (HUD), respectively. Both use formulas based
upon a grantee's number of AIDS cases, rather than HIV and AIDS cases, to
distribute funds to metropolitan areas, states, and territories. HIV cases
must be incorporated with AIDS cases in CARE Act formulas not later than
fiscal year 2007.

GAO was asked to examine (1) how CARE Act and HOPWA funds are allocated
among types of services, (2) the extent of funding distribution
differences among CARE Act and HOPWA grantees, and how funding formula
provisions contribute to these differences, and (3) what distribution
differences could result from incorporating HIV case counts in CARE Act
and HOPWA funding formulas.

What GAO Recommends

If Congress wishes CARE Act and HOPWA funding to more closely reflect the
distribution of persons living with AIDS, it should consider taking
actions that lead to more comparable funding per case by revising the
funding formulas. HHS and HUD generally agreed with GAO's identification
of issues in the funding formulas.

CARE Act and HOPWA grants are allocated by grantees for health care,
housing assistance, and a variety of services for people with HIV/AIDS.
These grants provide services for persons who have been diagnosed with HIV
that has not progressed to AIDS as well as those for whom it has. In
fiscal year 2003, more than half of Title I CARE Act funds awarded to
eligible metropolitan areas (EMAs) were allocated for health care services
such as outpatient care and home health services, and over two-thirds of
Title II CARE Act funds awarded to states and territories were allocated
for medications. Two-thirds of HOPWA funds were used for direct housing
costs for people with HIV/AIDS and their families.

Multiple provisions in the CARE Act and HOPWA grant funding formulas as
enacted result in funding not being comparable per AIDS case across
grantees. First, both the CARE Act and HOPWA use measures of AIDS cases
that do not accurately reflect the number of persons living with AIDS. For
example, the statutory funding formulas require the use of cumulative AIDS
case counts, which could include deceased cases. Second, AIDS cases within
EMAs are counted once for determining funding under Title I of the CARE
Act for EMAs and again under Title II for determining funding for the
states and territories in which those EMAs are located. As a result,
states with EMAs receive more total funding per case than states without
EMAs. Third, CARE Act hold-harmless provisions under Titles I and II and
the grandfather clause for EMAs under Title I sustain the funding and
eligibility of CARE Act grantees on the basis of a previous year's
measurements of the number of AIDS cases in these jurisdictions. For
example, under Title I's hold-harmless provision, one EMA continues to
have deceased AIDS cases factored into its allocation because its
hold-harmless funding dates back to the mid-1990s when formula funding was
based on a count of AIDS cases from the beginning of the epidemic.

If HIV case counts had been incorporated along with AIDS case counts in
allocating fiscal year 2004 CARE Act and HOPWA grants, funding would have
shifted among jurisdictions. Grantees in the South and the Midwest
generally would have received more funding, although there would have been
grantees that would have received increased funding and grantees that
would have received decreased funding in every region of the country.
Although CARE Act and HOPWA grantees have established HIV case reporting
systems, differences between these systems-in their maturity and reporting
methods, for instance-would impact the appropriateness of using HIV case
counts in distributing CARE Act and HOPWA funding. GAO found that CARE Act
and HOPWA fiscal year 2004 funding would have shifted to jurisdictions
with more mature HIV reporting systems.
*** End of document. ***