Exploring Changes in Racial/Ethnic Disparities of HIV Diagnosis Rates Under the “Ending the HIV Epidemic: A Plan for America” Initiative

Abstract

Objectives

Racial/ethnic disparities in HIV diagnosis rates remain despite the availability of effective treatment and prevention tools in the United States. In 2019, President Trump announced the “Ending the HIV Epidemic: A Plan for America” (EHE) initiative to reduce new HIV infections in the United States at least 75% by 2025 and at least 90% by 2030. The objective of this study was to show the potential effect of the EHE initiative on racial/ethnic disparities in HIV diagnosis rates at the national level.

Methods

We used 2017 HIV diagnoses data from the Centers for Disease Control and Prevention National HIV Surveillance System. We developed a counterfactual scenario to determine changes in racial/ethnic disparities if the 2017 HIV diagnosis rates were reduced by 75% in the geographic regions targeted by the EHE initiative. We used 4 measures to calculate results: rate ratio, population-attributable proportion (PAP), Gini coefficient, and Index of Disparity.

Results

The relative measures of racial/ethnic disparity decreased by 9%-21% in the EHE scenario compared with the 2017 HIV diagnoses data. The largest decrease was in the Hispanic/Latino:white rate ratio (−20.6%) and in the black:white rate ratio (−18.2%). The PAP measure decreased by 11.5%. The absolute versions of the Index of Disparity (unweighted and weighted) were approximately 50% lower in the EHE scenario than in the 2017 HIV diagnoses data.

Conclusions

EHE efforts could reduce but will not eliminate racial/ethnic disparities in HIV diagnosis rates. Efforts to address racial/ethnic disparities should continue, and innovative approaches, specifically those that focus on social and structural factors, should be developed and implemented for populations that are disproportionately affected by HIV in the United States.

Keywords

HIV diagnoses racial/ethnic disparities disparity measures social determinants of health

Advances in treatment and prevention services have reduced the incidence, morbidity, and mortality associated with HIV infection.^1

-4 Prevention and treatment tools that exist today have the potential to eliminate HIV transmission. People with HIV who adhere to antiretroviral treatment and achieve viral suppression have effectively no risk of sexually transmitting the virus to their HIV-negative partners.^1

-4 Furthermore, people at high risk of HIV infection can reduce their risk through daily use of preexposure prophylaxis and use of nonoccupational postexposure prophylaxis.^5

-8 Although HIV incidence remained stable in 2018 compared with 2014, approximately 36 400 new HIV infections occurred in 2018.⁹ Furthermore, racial/ethnic and geographic disparities in HIV persist: diagnosis rates are disproportionately higher among black/African American and Hispanic/Latino populations and in the South.⁹

In 2019, President Trump announced the “Ending the HIV Epidemic: A Plan for America” (EHE) initiative.¹⁰ The EHE initiative will use 3 key strategies—diagnose, treat, and prevent—to reduce new HIV infections in the United States by at least 75% by 2025 and by at least 90% by 2030.¹⁰ The EHE initiative will be implemented in multiple phases. During the first phase, resources, expertise, and technology will be infused in 48 US counties; Washington, DC; and San Juan, Puerto Rico—which together accounted for >50% of new HIV diagnoses in 2016 and 2017—and in 7 states (Alabama, Arkansas, Kentucky, Mississippi, Missouri, Oklahoma, and South Carolina) with substantial HIV burden in rural areas (ie, ≥10% of new HIV diagnoses in 2016 and 2017 were in rural areas).¹⁰

The objective of this study was to illustrate the potential effect of the EHE initiative on racial/ethnic disparities in HIV diagnosis rates at the national level. Our analysis is not an HIV transmission modeling study; we do not examine how the EHE initiative will achieve its goals, the relative importance of interventions such as HIV testing, or where to focus resources along the care continuum (testing, diagnosis, linkage to care, retention, and viral suppression). Rather, it is an illustration of the reductions in racial/ethnic disparity that would be achieved in a hypothetical scenario in which the EHE initiative leads to a uniform 75% reduction in HIV diagnoses across all racial/ethnic groups in the geographic areas targeted by the EHE initiative, without regard to the interventions used to achieve this reduction or to the feasibility of reaching the 75% goal in all targeted areas.

Methods

Data

We used 2017 data from AtlasPlus on new HIV diagnoses and population size for adults and adolescents aged ≥13 in the United States (excluding US territories) by racial/ethnic group.¹¹ We also used 2017 data on new HIV diagnoses and population size for adults and adolescents aged ≥13 by racial/ethnic group for the areas targeted by the EHE initiative from the National HIV Surveillance System (unpublished data, Centers for Disease Control and Prevention, 2017). We excluded data from US territories from our analyses because national totals in AtlasPlus do not include data for these areas. Although San Juan, Puerto Rico, is included in the geographic areas targeted by the EHE initiative, we did not include data for San Juan in the analyses because the data are not available by race/ethnicity.

We then used 4 measures to calculate racial/ethnic disparities in new HIV diagnosis rates (number of new HIV diagnoses per 100 000 population) for the 50 states and Washington, DC, among the following racial/ethnic groups: American Indian/Alaska Native, Asian, black/African American, Hispanic/Latino, Native Hawaiian/other Pacific Islander, white, and multiple races. We also examined a counterfactual scenario in which the reported HIV diagnosis rates in 2017 were reduced by 75% in the EHE targeted areas, to reflect the goals set by the EHE initiative to decrease new HIV diagnoses by 75% by 2025. In doing so, we calculated the number of HIV diagnoses in the 50 states and Washington, DC, when assuming that the rate of HIV diagnoses in the targeted areas was 75% lower (overall and for each racial/ethnic group considered) than reported for 2017 and assuming no change in HIV diagnosis rates in the areas not targeted. We then calculated disparities in HIV diagnosis rates for the 50 states and Washington, DC, in this counterfactual EHE scenario to illustrate the potential effect of the EHE initiative on racial/ethnic disparities in HIV diagnosis rates at the national level.

Disparity Measures

We used 4 relative measures of disparity: the rate ratio (the black:white rate ratio and the Hispanic/Latino:white rate ratio), 2 versions of the Index of Disparity, 2 versions of the population-attributable proportion (PAP), and the Gini coefficient.^12

-17 The Index of Disparity, PAP, and Gini coefficient are composite measures that account for disparities across the 7 racial/ethnic groups that we examined, whereas the rate ratio accounts for disparities between 2 specified racial/ethnic groups.^12

-17 We also applied 2 versions of the Index of Disparity to determine the absolute racial/ethnic disparity in HIV diagnosis rates: the absolute Index of Disparity and the weighted absolute Index of Disparity.^12

-17 Disparity measures are detailed elsewhere.^12

-17

We calculated the black:white rate ratio as the HIV diagnosis rate among black/African American people divided by the HIV diagnosis rate among white people, and we calculated the Hispanic/Latino:white rate ratio in an analogous manner.¹⁷

The Index of Disparity reflects the average of the absolute differences between HIV diagnosis rates for the 7 racial/ethnic groups we examined and the HIV diagnosis rate for the overall population, expressed in relative terms and as a percentage.¹⁴ We calculated the Index of Disparity as follows:

100 * (\frac{\sum_{i = 1}^{7} ∣ R a t e_{i} - R a t e_{o v e r a l l} ∣}{7}) ∕ R a t e_{o v e r a l l}

where i indicates the racial group, rate is the HIV diagnosis rate among people aged ≥13 in the given group, and the overall rate is the rate across all 7 racial/ethnic groups combined.

We calculated the weighted version of the Index of Disparity in an analogous manner, except that we calculated a population-weighted average of the absolute differences in HIV diagnosis rates between each group and the HIV diagnosis rate for the overall population, as follows:

100 * (\frac{\sum_{i = 1}^{7} ∣ R a t e_{i} - R a t e_{o v e r a l l} ∣ * P o p u l a t i o n_{i}}{P o p u l a t i o n_{o v e r a l l}}) ∕ R a t e_{o v e r a l l}

where population_i indicates the population size of the racial/ethnic group i and the overall population reflects the combined populations of all 7 racial/ethnic groups.^12,13,16 We calculated the absolute Index of Disparity and the weighted absolute Index of Disparity in the same manner as the Index of Disparity and the weighted Index of Disparity, respectively, except that we did not divide by the overall HIV diagnosis rate when calculating the absolute measures.^13,16

The PAP disparity measure reflects the change in HIV diagnosis rates that would be realized if the HIV diagnosis rates for all 7 racial/ethnic groups we examined were the same as for the comparison group, such as the group with the lowest HIV diagnosis rate.¹⁵ We calculated the PAP as follows:

P A P = \sum_{i = 1}^{i = 7} (C_{i} - {\hat{C}}_{i}) ∕ C,

where C_i is the number of HIV diagnoses in Group i, Ĉ_i is the number of HIV diagnoses that would have been in Group i if Group i had the same HIV diagnosis rate as that of the comparison group, and C is the total number of HIV diagnoses across all 7 racial/ethnic groups.^12,16,18 We calculated 2 versions of the PAP: 1 version in which the comparison group was the group with the lowest HIV diagnosis rate and 1 version in which the comparison group was white people.

The Gini coefficient is a statistical measure of economic inequality in a population that has been adapted and applied in research on sexually transmitted disease prevention.¹² To calculate the Gini coefficient, we ranked the racial/ethnic groups from 1 to 7 according to their HIV diagnosis rates (i = 1 and i = 7 denote the group with the lowest and highest rates, respectively). We calculated the Gini coefficient (G) as:

G = 1 - \sum_{i = 1}^{i = 7} (Y_{i} + Y_{i - 1}) (X_{i} - X_{i - 1})

where Y_i and X_i are the cumulative percentage of HIV diagnoses and the cumulative percentage of the population, respectively, accounted for by Group 1 through Group i, and X₀ and Y₀ are both 0.¹²

Results

For the 7 racial/ethnic groups we examined, 38 182 HIV diagnoses were reported in 2017: 22 386 in EHE-targeted areas and 15 796 in non–EHE-targeted areas (Table 1). In the EHE scenario in which we assumed a 75% reduction in HIV diagnosis rates in the targeted areas, we estimated 21 393 diagnoses: 5597 in EHE-targeted areas and 15 796 in non–EHE-targeted areas.

Table 1

Inputs used to calculate disparity measures of HIV infection among adults and adolescents aged ≥13, by racial/ethnic group, as reported in 2017 and as estimated for the hypothetical scenario in which HIV diagnoses are reduced by 75% in targeted areas^a

Inputs	Race/ethnicity
Inputs	American Indian/Alaska Native	Asian	Black/African American	Hispanic/Latino	Native Hawaiian/other Pacific Islander	White	Multiple races	Total
Population
National	1 958 438	15 761 316	33 405 323	45 335 362	470 527	171 504 251	4 545 029	272 980 246
EHE-targeted areas	603 209	7 942 165	18 287 593	23 068 076	161 329	49 041 560	1 720 796	100 824 728
Non–EHE-targeted areas	1 355 229	7 819 151	15 117 730	22 267 286	309 198	122 462 691	2 824 233	172 155 518
Reported HIV diagnoses: 2017
National	212	939	16 630	9442	56	10 038	865	38 182
EHE-targeted areas	83	594	10 379	6092	24	4685	529	22 386
Non–EHE-targeted areas	129	345	6251	3350	32	5353	336	15 796
HIV diagnoses: hypothetical EHE scenario
National	150	494	8846	4873	38	6524	468	21 393
EHE-targeted areas	21	149	2595	1523	6	1171	132	5597
Non–EHE-targeted areas	129	345	6251	3350	32	5353	336	15 796

^aAll values are numbers. The “Ending the HIV Epidemic in America” (EHE) initiative is a US Department of Health and Human Services initiative to reduce new HIV infections by at least 75% by 2025 and by at least 90% by 2030.¹⁰

The relative measures of racial/ethnic disparities in HIV diagnosis rates decreased by a range of 9%-21% in the hypothetical EHE scenario compared with 2017 HIV diagnoses data (Table 2). The largest decreases were in the Hispanic/Latino:white rate ratio (−20.6%) and the black:white ratio (−18.2%). The PAP measure decreased by 11.5%, from 0.582 to 0.515.

Table 2

Disparity measures calculated using reported HIV diagnoses in 2017 and using estimated HIV diagnoses for the hypothetical EHE scenario^a

Disparity measure^b	Using reported HIV diagnoses in 2017	Hypothetical EHE scenario	Percentage difference in disparity measure in hypothetical EHE scenario vs 2017 data
Relative disparity measures
Black:white rate ratio	8.5	7.0	−18.2
Hispanic:white rate ratio	3.6	2.8	−20.6
Index of Disparity	70.6	60.5	−14.3
Index of Disparity, weighted	80.1	71.6	−10.6
Population-attributable proportion^c	0.582	0.515	−11.5
Gini coefficient	0.450	0.409	−9.0
Absolute disparity measures
Absolute Index of Disparity	987.0	474.1	−52.0
Absolute Index of Disparity, weighted	1120.1	561.3	−49.9

^aThe “Ending the HIV Epidemic in America” (EHE) initiative is a US Department of Health and Human Services initiative to reduce new HIV infections by at least 75% by 2025 and by at least 90% by 2030.¹⁰

^bThe disparity measures are defined in the Methods section.

^cThe population-attributable proportion (PAP) was calculated when using HIV diagnoses rates among white people as the comparator. The PAP measure when using the group with the lowest rate as the comparator (not shown in table) yielded an unbalanced comparison across scenarios, because white people had the lowest reported HIV diagnosis rate in 2017 (PAP = 0.582) and Asian people had the lowest rate in the EHE scenario (PAP = 0.600).

The differences in the absolute disparity measures across the 2 scenarios we examined were more pronounced than were the differences in relative disparity measures. Both versions of the absolute Index of Disparity (unweighted and weighted) were about 50% lower in the EHE scenario than when using 2017 HIV diagnoses data (Table 2).

Discussion

Nationally, racial/ethnic disparities in HIV diagnosis rates in the United States persist despite the availability of effective treatment and prevention tools. The EHE initiative seeks to reduce HIV transmissions during the next 10 years by first deploying resources and technology to geographic areas most affected by HIV before eventually expanding nationwide.¹⁰ Evidence suggests that targeting these geographic areas can be an effective way to address racial/ethnic disparities in HIV diagnosis rates even if such disparities are not explicitly considered when setting the geographic targets.¹³ Consistent with this evidence, our analysis of multiple measures of relative and absolute disparities using 2017 HIV diagnoses data indicated that notable reductions in racial/ethnic disparities would be attained if the 5-year goal of reducing new HIV infections by 75% is achieved in the geographic areas targeted by the EHE initiative.

Results from the relative disparity measures we examined suggested that the EHE initiative could reduce relative disparities in HIV diagnoses by 9%-21%, with the greatest reduction (21%) occurring in the Hispanic/Latino:white rate ratio. The 11.5% decline in the PAP measure suggests that the percentage of HIV diagnoses attributable to racial/ethnic disparities in HIV would decline from 58% to 51% because of the EHE initiative. The decrease in relative disparities in the ETE scenario can be explained by the higher proportion of disproportionately affected populations that reside in the EHE-targeted areas compared with the non–EHE-targeted areas. Results from the absolute racial/ethnic disparity measures suggest that disparities in HIV diagnosis rates could be reduced by about half if the 5-year goal of the EHE initiative is achieved. The reduction in absolute disparities is more applicable than the reduction in relative disparities to illustrate the potential decrease in the absolute number of HIV infections that could be achieved through the EHE initiative.

Although the EHE initiative has the potential to reduce racial/ethnic disparities, this result will not be fully realized unless every person with or at risk for HIV benefits from effective treatment and prevention services.¹⁹ Data indicate that racial/ethnic minority communities have poorer HIV care outcomes (eg, engagement in care and viral suppression rates) than white people.²⁰ Furthermore, compared with some white communities, fewer racial/ethnic minority communities are aware of and use effective HIV prevention tools such as preexposure prophylaxis.²¹ These poorer outcomes are associated with social and structural factors, such as lack of health insurance and access to quality health care,²² HIV-related stigma,²³ homelessness,^24,25 substance misuse,²⁶ mental illness,^27,28 delays in linkage to care,²⁹ and health care provider/staff implicit and conscious bias based on race, sex, sexual identity/orientation, and gender identity.³⁰ Therefore, efforts to reduce HIV-related disparities under the EHE initiative and overall should focus on these factors. The key is to identify the factors that impede progress under each EHE strategy and develop effective interventions and strategies to address each factor once identified.³¹

Limitations

This study had several limitations. First, our study used HIV diagnoses data, whereas the EHE initiative will use HIV incidence data to monitor progress. Currently, HIV incidence data are not available by race/ethnicity within geographic location. We believe, however, that the diagnoses data can serve as a proxy for this pre-EHE analysis. Second, the hypothetical scenario we examined did not account for the increase in HIV diagnoses that may occur because of the focus on increasing HIV testing under the EHE initiative. This limitation could affect results in the disparity measures. Third, we excluded data from US territories; had we included data from Puerto Rico, the effect of the EHE initiative on the Hispanic/Latino population might have been even more pronounced than we estimated. Fourth, we assumed no changes in new HIV diagnoses in non–EHE-targeted jurisdictions. Diagnosis rates might change nationally and in non–EHE-targeted regions because of the EHE planning process. Fifth, we assumed that EHE resources would be targeted based only on geographic area. If EHE resources in each geographic area are efficiently targeted toward populations in greatest need, the reductions in racial/ethnic disparities would be even greater than our results suggest. Finally, our analysis is an illustration not an HIV transmission modeling study and did not consider any interventions needed to reach the 75% EHE goal in all targeted areas.^19,32 The objective of our study was to illustrate potential changes in racial/ethnic disparities if the 75% EHE goal is uniformly achieved across all racial/ethnic groups.

Conclusion

Our analysis indicated that the EHE initiative could result in substantial strides toward reducing racial/ethnic disparities in HIV diagnosis rates. Achieving the EHE goals will depend, in part, on building strong partnerships between federal agencies and key partners in targeted geographic areas (eg, city, county, and state public health departments; tribal communities; local and regional clinics; health care facilities; clinicians; providers of medication-assisted treatment for opioid use disorder; professional associations; advocates; community- and faith-based organizations; foundations; private sector; and academic and research institutions).¹⁰ Engaging local partners will enhance the development and implementation of appropriate strategies to address the needs of priority groups in affected communities. EHE efforts will not, however, eliminate disparities. To augment the effect of the EHE initiative, efforts to address disparities should continue, and innovative approaches, especially approaches that include a focus on social and structural factors, should be developed and implemented for populations disproportionately affected by HIV in the United States.

Footnotes

Acknowledgments

The authors thank our colleagues at the Centers for Disease Control and Prevention for their review of and feedback on this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors declared no financial support with respect to the research, authorship, and/or publication of this article.

ORCID iDs

Donna Hubbard McCree

Harrell Chesson

Zanetta Gant

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