Optimal Allocation of Societal HIV Prevention Resources to Reduce HIV Incidence in the United States.

Objectives. To optimize combined public and private spending on HIV prevention to achieve maximum reductions in incidence.Methods. We used a national HIV model to estimate new infections from 2018 to 2027 in the United States. We estimated current spending on HIV screening, interventions that move persons with diagnosed HIV along the HIV care continuum, pre-exposure prophylaxis, and syringe services programs. We compared the current funding allocation with 2 optimal scenarios: (1) a limited-reach scenario with expanded efforts to serve eligible persons and (2) an ideal, unlimited-reach scenario in which all eligible persons could be served.Results. A continuation of the current allocation projects 331 000 new HIV cases over the next 10 years. The limited-reach scenario reduces that number by 69%, and the unlimited reach scenario by 94%. The most efficient funding allocations resulted in prompt diagnosis and sustained viral suppression through improved screening of high-risk persons and treatment adherence support for those infected.Conclusions. Optimal allocations of public and private funds for HIV prevention can achieve substantial reductions in new infections. Achieving reductions of more than 90% under current funding will require that virtually all infected receive sustained treatment.

Health Utility Estimates and Their Application to HIV Prevention in the United States: Implications for Cost-Effectiveness Modeling and Future Research Needs.

Objectives. Health utility estimates from the current era of HIV treatment, critical for cost-effectiveness analyses (CEA) informing HIV health policy, are limited. We examined peer-reviewed literature to assess the appropriateness of commonly referenced utilities, present previously unreported quality-of-life data from two studies, and discuss future implications for HIV-related CEA. Methods. We searched a database of cost-effectiveness analyses specific to HIV prevention efforts from 1999 to 2016 to identify the most commonly referenced sources for health utilities and to examine practices around using and reporting health utility data. Additionally, we present new utility estimates from the Centers of Disease Control and Prevention's Medical Monitoring Project (MMP) and the INSIGHT Strategies for Management of Anti-Retroviral Therapy (SMART) trial. We compare data collection time frames, sample characteristics, assessment methods, and key estimates. Results. Data collection for the most frequently cited utility estimates ranged from 1985 to 1997, predating modern HIV treatment. Reporting practices around utility weights are poor and lack details on participant characteristics, which may be important stratifying factors for CEA. More recent utility estimates derived from MMP and SMART were similar across CD4+ count strata and had a narrower range than pre-antiretroviral therapy (ART) utilities. Conclusions. Despite the widespread use of ART, cost-effectiveness analysis of HIV prevention interventions frequently apply pre-ART health utility weights. Use of utility weights reflecting the current state of the US epidemic are needed to best inform HIV research and public policy decisions. Improved practices around the selection, application, and reporting of health utility data used in HIV prevention CEA are needed to improve transparency.

Estimating the costs and cost-effectiveness of HIV self-testing among men who have sex with men, United States.

INTRODUCTION: HIV testing is an essential prerequisite for accessing treatment with antiretroviral therapy or prevention using pre-exposure prophylaxis. Internet distribution of HIV self-tests is a novel approach, and data on the programmatic cost of this approach are limited. We analyse the costs and cost-effectiveness of a self-testing programme. METHODS: Men who have sex with men (MSM) reporting unknown or negative HIV status were enrolled from March to August 2015 into a 12-month trial of HIV self-testing in the United States. Participants were randomly assigned either to the self-testing arm or the control arm. All participants received information on HIV testing services and locations in their community. Self-testing participants received up to four self-tests each quarter, which they could use themselves or distribute to their social network associates. Quarterly follow-up surveys collected testing outcomes, including number of tests used and new HIV diagnoses. Using trial expenditure data, we estimated the cost of implementing a self-testing programme. Primary outcomes of this analysis included total programme implementation costs, cost per self-test completed, cost per person tested, cost per new HIV diagnosis among those self-tested and cost per quality adjusted life year (QALY) saved. RESULTS: A total of 2665 men were assigned either to the self-testing arm (n = 1325) or the control arm (n = 1340). HIV testing was reported by 971 self-testing participants who completed a total of 5368 tests. In the control arm, 619 participants completed 1463 HIV tests. The self-testing participants additionally distributed 2864 self-tests to 2152 social network associates. Testing during the trial identified 59 participants and social network associates with newly diagnosed HIV infection in the self-testing arm; 11 control participants were newly diagnosed with HIV. The implementation cost of the HIV self-testing programme was $449,510. The cost per self-test completed, cost per person tested at least once, and incremental cost per new HIV diagnosis was $61, $145 and $9365 respectively. We estimated that self-testing programme potentially averted 3.34 transmissions, saved 14.86 QALYs and nearly $1.6 million lifetime HIV treatment costs. CONCLUSIONS: The HIV self-testing programme identified persons with newly diagnosed HIV infection at low cost, and the programme is cost saving.

Optimal allocation of HIV prevention funds for state health departments.

OBJECTIVE: To estimate the optimal allocation of Centers for Disease Control and Prevention (CDC) HIV prevention funds for health departments in 52 jurisdictions, incorporating Health Resources and Services Administration (HRSA) Ryan White HIV/AIDS Program funds, to improve outcomes along the HIV care continuum and prevent infections. METHODS: Using surveillance data from 2010 to 2012 and budgetary data from 2012, we divided the 52 health departments into 5 groups varying by number of persons living with diagnosed HIV (PLWDH), median annual CDC HIV prevention budget, and median annual HRSA expenditures supporting linkage to care, retention in care, and adherence to antiretroviral therapy. Using an optimization and a Bernoulli process model, we solved for the optimal CDC prevention budget allocation for each health department group. The optimal allocation distributed the funds across prevention interventions and populations at risk for HIV to prevent the greatest number of new HIV cases annually. RESULTS: Both the HIV prevention interventions funded by the optimal allocation of CDC HIV prevention funds and the proportions of the budget allocated were similar across health department groups, particularly those representing the large majority of PLWDH. Consistently funded interventions included testing, partner services and linkage to care and interventions for men who have sex with men (MSM). Sensitivity analyses showed that the optimal allocation shifted when there were differences in transmission category proportions and progress along the HIV care continuum. CONCLUSION: The robustness of the results suggests that most health departments can use these analyses to guide the investment of CDC HIV prevention funds into strategies to prevent the most new cases of HIV.

Combinations of interventions to achieve a national HIV incidence reduction goal: insights from an agent-based model.

OBJECTIVE: Analyzing HIV care service targets for achieving a national goal of a 25% reduction in annual HIV incidence and evaluating the use of annual HIV diagnoses to measure progress in incidence reduction. DESIGN: Because there are considerable interactions among HIV care services, we model the dynamics of 'combinations' of increases in HIV care continuum targets to identify those that would achieve 25% reductions in annual incidence and diagnoses. METHODS: We used Progression and Transmission of HIV/AIDS 2.0, an agent-based dynamic stochastic simulation of HIV in the United States. RESULTS: A 25% reduction in annual incidence could be achieved by multiple alternative combinations of percentages of persons with diagnosed infection and persons with viral suppression including 85 and 68%, respectively, and 90 and 59%, respectively. The first combination corresponded to an 18% reduction in annual diagnoses, and infections being diagnosed at a median CD4 cell count of 372 cells/µl or approximately 3.8 years from time of infection. The corresponding values on the second combination are 4%, 462 cells/µl, and 2.0 years, respectively. CONCLUSION: Our analysis provides policy makers with specific targets and alternative choices to achieve the goal of a 25% reduction in HIV incidence. Reducing annual diagnoses does not equate to reducing annual incidence. Instead, progress toward reducing incidence can be measured by monitoring HIV surveillance data trends in CD4 cell count at diagnosis along with the proportion who have achieved viral suppression to determine where to focus local programmatic efforts.

Cost Effectiveness of HIV Prevention Interventions in the U.S.

INTRODUCTION: The purpose of this study was to assess and compare the cost effectiveness of current HIV prevention interventions in the U.S. using a consistent, standardized methodology. METHODS: The cost effectiveness of common and emerging HIV biomedical and behavioral prevention interventions as delivered to men who have sex with men, injection drug users, and sexually active heterosexuals was estimated. Data on program costs, intervention efficacy, risk behaviors, and per contact transmission probabilities were collected from peer-reviewed papers and health department reports. These data were combined with 2010 national HIV incidence and prevalence surveillance data in a Bernoulli process model to estimate the reduced annual risk of HIV transmission or acquisition associated with these interventions. The cost per prevented case of HIV and the cost per saved quality-adjusted life year were then calculated. Analyses were conducted between 2014 and 2015. RESULTS: Interventions to diagnose HIV and provide ongoing care and treatment had the lowest cost per prevented case. Among interventions targeted at specific risk groups, interventions for men who have sex with men were the most cost effective. The least cost-effective interventions typically addressed people at risk of acquiring HIV rather than those at risk of transmitting the disease. CONCLUSIONS: HIV prevention interventions targeted at high-risk populations, those associated with the care continuum, and those that reduce the transmission risk of HIV-infected people are typically the most cost effective. Decision makers can consider these results in planning an efficient allocation of HIV prevention resources.

Cost-Effectiveness of Frequent HIV Testing of High-Risk Populations in the United States.

PURPOSE: Data showing a high incidence of HIV infection among men who have sex with men (MSM) who had annual testing suggest that more frequent HIV testing may be warranted. Testing technology is also a consideration given the availability of sensitive testing modalities and the increased use of less-sensitive rapid, point-of-care antibody tests. We assessed the cost-effectiveness of HIV testing of MSM and injection drug users (IDUs) at 3- and 6-month intervals using fourth-generation and rapid tests. METHODS: We used a published mathematical model of HIV transmission to evaluate testing intervals for each population using cohorts of 10,000 MSM and IDU. We incorporated HIV transmissions averted due to serostatus awareness and viral suppression. We included costs for HIV testing and treatment initiation, and also treatment costs saved from averted transmissions. RESULTS: For MSM, HIV testing was cost saving or cost effective over a 1-year period for both 6-month compared with annual testing and quarterly compared with 6-month testing using either test. Testing IDU every 6 months compared with annually was moderately cost effective over a 1-year period with a fourth-generation test, while testing with rapid, point-of-care tests or quarterly was not cost effective. MSM results remained robust in sensitivity analysis, whereas IDU results were sensitive to changes in HIV incidence and continuum-of-care parameters. Threshold analyses on costs suggested that additional implementation costs could be incurred for more frequent testing for MSM while remaining cost effective. CONCLUSIONS: HIV testing of MSM as frequently as quarterly is cost effective compared with annual testing, but testing IDU more frequently than annually is generally not cost effective.

From Theory to Practice: Implementation of a Resource Allocation Model in Health Departments.

OBJECTIVE: To develop a resource allocation model to optimize health departments' Centers for Disease Control and Prevention (CDC)-funded HIV prevention budgets to prevent the most new cases of HIV infection and to evaluate the model's implementation in 4 health departments. DESIGN, SETTINGS, AND PARTICIPANTS: We developed a linear programming model combined with a Bernoulli process model that allocated a fixed budget among HIV prevention interventions and risk subpopulations to maximize the number of new infections prevented. The model, which required epidemiologic, behavioral, budgetary, and programmatic data, was implemented in health departments in Philadelphia, Chicago, Alabama, and Nebraska. MAIN OUTCOME MEASURES: The optimal allocation of funds, the site-specific cost per case of HIV infection prevented rankings by intervention, and the expected number of HIV cases prevented. RESULTS: The model suggested allocating funds to HIV testing and continuum-of-care interventions in all 4 health departments. The most cost-effective intervention for all sites was HIV testing in nonclinical settings for men who have sex with men, and the least cost-effective interventions were behavioral interventions for HIV-negative persons. The pilot sites required 3 to 4 months of technical assistance to develop data inputs and generate and interpret the results. Although the sites found the model easy to use in providing quantitative evidence for allocating HIV prevention resources, they criticized the exclusion of structural interventions and the use of the model to allocate only CDC funds. CONCLUSIONS: Resource allocation models have the potential to improve the allocation of limited HIV prevention resources and can be used as a decision-making guide for state and local health departments. Using such models may require substantial staff time and technical assistance. These model results emphasize the allocation of CDC funds toward testing and continuum-of-care interventions and populations at highest risk of HIV transmission.

Nearly Half Of US Adults Living With HIV Received Federal Disability Benefits In 2009.

The effects of HIV infection on national labor-force participation have not been rigorously evaluated. Using data from the Medical Monitoring Project and the National Health Interview Survey, we present nationally representative estimates of the receipt of disability benefits by adults living with HIV receiving care compared with the general US adult population. We found that in 2009, adults living with HIV were nine times more likely than adults in the general population to receive disability benefits. The risk of being on disability is also greater for younger and more educated adults living with HIV compared to the general population, which suggests that productivity losses can result from HIV infection. To prevent disability, early diagnosis and treatment of HIV are essential. This study offers a baseline against which to measure the impacts of recently proposed or enacted changes to Medicaid and private insurance markets, including the Affordable Care Act and proposed revisions to the Social Security Administration's HIV Infection Listings.

A systematic review on cost effectiveness of HIV prevention interventions in the United States.

BACKGROUND: The Centers for Disease Control and Prevention (CDC) focus on funding HIV prevention interventions likely to have high impact on the HIV epidemic. In its most recent funding announcement to state and local health department grantees, CDC required that health departments allocate the majority of funds to four HIV prevention interventions: HIV testing, prevention with HIV-positives and their partners, condom distribution and policy initiatives. OBJECTIVE: We conducted a systematic review of the published literature to determine the extent of the cost-effectiveness evidence for each of those interventions. METHODOLOGY: We searched for US-based studies published through October 2012. The studies that qualified for inclusion contained original analyses that reported costs per quality-adjusted life-year saved, life-year saved, HIV infection averted, or new HIV diagnosis. For each study, paired reviewers performed a detailed review and data extraction. We reported the number of studies related to each intervention and summarized key cost-effectiveness findings according to intervention type. Costs were converted to 2011 US dollars. RESULTS: Of the 50 articles that met the inclusion criteria, 33 related to HIV testing, 15 assessed prevention with HIV-positives and partners, three reported on condom distribution, and one reported on policy initiatives. Methodologies and cost-effectiveness metrics varied across studies and interventions, making them difficult to compare. CONCLUSION: Our review provides an updated summary of the published evidence of cost effectiveness of four key HIV prevention interventions recommended by CDC. With the exception of testing-related interventions, including partner services, where economic evaluations suggest that testing often can be cost effective, more cost-effectiveness research is needed to help guide the most efficient use of HIV prevention funds.

Estimating the cost to U.S. health departments to conduct HIV surveillance.

OBJECTIVES: HIV case surveillance is a primary source of information for monitoring HIV burden in the United States and guiding the allocation of prevention and treatment funds. While the number of people living with HIV and the need for surveillance data have increased, little is known about the cost of surveillance. We estimated the economic cost to health departments of conducting high-quality HIV case surveillance. METHODS: We collected primary data on the unit cost and quantity of resources used to operate the HIV case surveillance program in Michigan, where HIV burden (i.e., the number of HIV cases) is moderate to high (n=14,864 cases). Based on Michigan's data, we projected the expected annual HIV surveillance cost for U.S., state, local, and territorial health departments. We based our cost projection on the variation in the number of new and established cases, area-specific wages, and potential economies of scale. RESULTS: We estimated the annual total HIV surveillance cost to the Michigan health department to be $1,286,524 ($87/case), the annual total cost of new cases to be $108,657 ($133/case), and the annual total cost of established cases to be $1,177,867 ($84/case). Our projected median annual HIV surveillance cost per health department ranged from $210,600 in low-HIV burden sites to $1,835,000 in high-HIV burden sites. CONCLUSIONS: Our analysis shows that a systematic approach to costing HIV surveillance at the health department level is feasible. For HIV surveillance, a substantial portion of total surveillance costs is attributable to maintaining established cases.

Updates of lifetime costs of care and quality-of-life estimates for HIV-infected persons in the United States: late versus early diagnosis and entry into care.

BACKGROUND: Lifetime costs of care and quality-of-life estimates for HIV-infected persons depend on the disease stage at which these persons are diagnosed, enter care, and start antiretroviral therapy. Updated estimates were used to analyze the effects of late versus early diagnosis/entry on US lifetime care costs, quality-of-life estimates, and HIV transmissions. METHODS: The Progression and Transmission of HIV/AIDS model was used to estimate discounted (3%) lifetime treatment costs ($US 2011) and quality-of-life variables from time of infection for cohorts of 10,000 HIV-infected index patients in 4 categories of CD4 count at diagnosis: (I) ≤200 cells/µL, (II) 201-350 cells/µL, (III) 351-500 cells/µL, and (IV) 501-900 cells/µL. It is assumed that index patient diagnoses were uniformly distributed across the CD4 count range in each category and that patients entered care at the time of diagnosis, remained in care, and were eligible to initiate antiretroviral therapy at a CD4 count of 500 cells/µL. Lifetime transmissions of the index patients were also estimated. RESULTS: Discounted average lifetime costs varied from $253,000 for category I index patients to $402,000 for category IV patients. Discounted quality-adjusted life years lost decreased from 7.95 to 4.45 across these categories, additional years of life expectancy increased from 30.8 to 38.1, and lifetime transmissions decreased from 1.40 to 0.72. CONCLUSIONS: Early diagnosis and treatment of HIV infection increases lifetime costs but improves length and quality of life and reduces the number of new infections transmitted by nearly 50%.

Estimating the impact of state budget cuts and redirection of prevention resources on the HIV epidemic in 59 California local health departments.

BACKGROUND: In the wake of a national economic downturn, the state of California, in 2009-2010, implemented budget cuts that eliminated state funding of HIV prevention and testing. To mitigate the effect of these cuts remaining federal funds were redirected. This analysis estimates the impact of these budget cuts and reallocation of resources on HIV transmission and associated HIV treatment costs. METHODS AND FINDINGS: We estimated the effect of the budget cuts and reallocation for California county health departments (excluding Los Angeles and San Francisco) on the number of individuals living with or at-risk for HIV who received HIV prevention services. We used a Bernoulli model to estimate the number of new infections that would occur each year as a result of the changes, and assigned lifetime treatment costs to those new infections. We explored the effect of redirecting federal funds to more cost-effective programs, as well as the potential effect of allocating funds proportionately by transmission category. We estimated that cutting HIV prevention resulted in 55 new infections that were associated with $20 million in lifetime treatment costs. The redirection of federal funds to more cost-effective programs averted 15 HIV infections. If HIV prevention funding were allocated proportionately to transmission categories, we estimated that HIV infections could be reduced below the number that occurred annually before the state budget cuts. CONCLUSIONS: Reducing funding for HIV prevention may result in short-term savings at the expense of additional HIV infections and increased HIV treatment costs. Existing HIV prevention funds would likely have a greater impact on the epidemic if they were allocated to the more cost-effective programs and the populations most likely to acquire and transmit the infection.

Allocating HIV prevention funds in the United States: recommendations from an optimization model.

The Centers for Disease Control and Prevention (CDC) had an annual budget of approximately $327 million to fund health departments and community-based organizations for core HIV testing and prevention programs domestically between 2001 and 2006. Annual HIV incidence has been relatively stable since the year 2000 and was estimated at 48,600 cases in 2006 and 48,100 in 2009. Using estimates on HIV incidence, prevalence, prevention program costs and benefits, and current spending, we created an HIV resource allocation model that can generate a mathematically optimal allocation of the Division of HIV/AIDS Prevention's extramural budget for HIV testing, and counseling and education programs. The model's data inputs and methods were reviewed by subject matter experts internal and external to the CDC via an extensive validation process. The model projects the HIV epidemic for the United States under different allocation strategies under a fixed budget. Our objective is to support national HIV prevention planning efforts and inform the decision-making process for HIV resource allocation. Model results can be summarized into three main recommendations. First, more funds should be allocated to testing and these should further target men who have sex with men and injecting drug users. Second, counseling and education interventions ought to provide a greater focus on HIV positive persons who are aware of their status. And lastly, interventions should target those at high risk for transmitting or acquiring HIV, rather than lower-risk members of the general population. The main conclusions of the HIV resource allocation model have played a role in the introduction of new programs and provide valuable guidance to target resources and improve the impact of HIV prevention efforts in the United States.

Cost effectiveness of the National HIV/AIDS Strategy goal of increasing linkage to care for HIV-infected persons.

BACKGROUND: One of the goals of the National HIV/AIDS Strategy (NHAS) is to increase the proportion of HIV-infected individuals linked to care within 3 months of diagnosis (early linkage) from 65% to 85%. Earlier access to care, and eventually, to treatment, increases life expectancy and quality of life for HIV-infected persons. However, longer treatment is also associated with higher costs, especially for antiretroviral drugs. We evaluated the cost effectiveness of achieving the NHAS goal and estimated the maximum cost that HIV programs could spend on linkage to care and remain cost effective. METHODS: We used the Progression and Transmission of HIV/AIDS model to estimate the effects on life measures and costs associated with increasing early linkage to care from 65% to 85%. We estimated an incremental cost-effectiveness ratio as the additional cost required to reach the target divided by the quality-adjusted life years (QALYs) gained and assumed that programs costing $100,000 or less per QALY gained are cost effective. RESULTS: Achieving the NHAS linkage-to-care goal increased life expectancy by 0.4 years and delayed the onset of AIDS by 1.2 years on average for every HIV-diagnosed person. Increasing early linkage to care cost an extra $62,200 per QALY gained, considering only benefits to index persons. The maximum that could be cost effectively spent on early linkage-to-care interventions was approximately $5100 per HIV-diagnosed person. CONCLUSIONS: Considerable investment can be cost effectively made to achieve the NHAS goal on early linkage to care.

Comparison of methods for estimating the cost of human immunodeficiency virus-testing interventions.

CONTEXT: The Centers for Disease Control and Prevention (CDC), Division of HIV/AIDS Prevention, spends approximately 50% of its $325 million annual human immunodeficiency virus (HIV) prevention funds for HIV-testing services. An accurate estimate of the costs of HIV testing in various settings is essential for efficient allocation of HIV prevention resources. OBJECTIVES: To assess the costs of HIV-testing interventions using different costing methods. DESIGN, SETTINGS, AND PARTICIPANTS: We used the microcosting-direct measurement method to assess the costs of HIV-testing interventions in nonclinical settings, and we compared these results with those from 3 other costing methods: microcosting-staff allocation, where the labor cost was derived from the proportion of each staff person's time allocated to HIV testing interventions; gross costing, where the New York State Medicaid payment for HIV testing was used to estimate program costs, and program budget, where the program cost was assumed to be the total funding provided by Centers for Disease Control and Prevention. MAIN OUTCOME MEASURES: Total program cost, cost per person tested, and cost per person notified of new HIV diagnosis. RESULTS: The median costs per person notified of a new HIV diagnosis were $12 475, $15 018, $2697, and $20 144 based on microcosting-direct measurement, microcosting-staff allocation, gross costing, and program budget methods, respectively. Compared with the microcosting-direct measurement method, the cost was 78% lower with gross costing, and 20% and 61% higher using the microcosting-staff allocation and program budget methods, respectively. CONCLUSIONS: Our analysis showed that HIV-testing program cost estimates vary widely by costing methods. However, the choice of a particular costing method may depend on the research question being addressed. Although program budget and gross-costing methods may be attractive because of their simplicity, only the microcosting-direct measurement method can identify important determinants of the program costs and provide guidance to improve efficiency.

How much should we pay for a new HIV diagnosis? A mathematical model of HIV screening in US clinical settings.

OBJECTIVE: To develop a model to assist clinical setting decision makers in determining how much they can spend on human immunodeficiency virus (HIV) screening and still be cost-effective. DESIGN: The authors developed a simple mathematical model relating the program cost per new HIV diagnosis to the cost per HIV infection averted and the cost per quality-adjusted life year (QALY) saved by screening. They estimated outcomes based on behavioral changes associated with awareness of HIV infection and applied the model to US sexually transmitted disease clinics. METHODS: The authors based the cost per new HIV diagnosis (2009 US dollars) on the costs of testing and the proportion of persons who tested positive. Infections averted were calculated from the reduction in annual transmission rates between persons aware and unaware of their infections. The authors defined program costs from the sexually transmitted disease clinic perspective and treatment costs and QALYs saved from the societal perspective. They undertook numerous sensitivity analyses to determine the robustness of the base case results. RESULTS: In the base case, the cost per new HIV diagnosis was $2528, the cost per infection averted was $40,516, and the cost per QALY saved was less than zero, or cost-saving. Given the model inputs, the cost per new diagnosis could increase to $22,909 to reach the cost-saving threshold and to $63,053 for the cost-effectiveness threshold. All sensitivity analyses showed that the cost-effectiveness results were consistent for extensive variation in the values of model inputs. CONCLUSIONS: HIV screening in a clinical setting is cost-effective for a wide range of testing costs, variations in positivity rates, reductions in HIV transmissions, and variation in the receipt of test results.

Return on public health investment: CDC's Expanded HIV Testing Initiative.

BACKGROUND: Over a 3-year period, the Centers for Disease Control and Prevention invested $102.3 million in a large-scale HIV testing program, the Expanded HIV Testing Initiative for populations disproportionally affected by HIV. Policy makers, who must optimize public health given a set budget, are interested in the financial return on investment (ROI) of large-scale HIV testing. METHODS: We conducted an ROI analysis using expenditure and outcome data from the program. A health system perspective was used that included all program expenditures including medical costs of treating newly diagnosed patients. We incorporated benefits of HIV transmissions averted from persons diagnosed of their infection through the Initiative compared with when, on average, those persons would have been diagnosed without the Initiative (3 years later in the base case). HIV transmissions were derived from a published mathematical model of HIV transmission. In sensitivity analysis, we tested the effect of 1-year to 5-year alternate testing intervals and differences in the prevalence of undiagnosed HIV infection. RESULTS: Under the Initiative, 2.7 million persons were tested for HIV, there was a newly diagnosed HIV positivity rate of 0.7%, and an estimated 3381 HIV infections were averted. It achieved a return of $1.95 for every dollar invested. ROI ranged from $1.46 to $2.01 for alternative testing intervals of 1-5 years and remained above $1 (positive return on investment) with a prevalence of undiagnosed HIV infection as low as 0.12%. CONCLUSIONS: The expanded testing Initiative yielded ROI values of >$1 under a broad range of sensitivity analyses and provides further support for large-scale HIV testing programs.