S4HARA: System for HIV/AIDS resource allocation

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Cost-Effectiveness of Newborn Circumcision in Reducing Lifetime HIV Risk among U.S. Males

BACKGROUND: HIV incidence was substantially lower among circumcised versus uncircumcised heterosexual African men in three clinical trials. Based on those findings, we modeled the potential effect of newborn male circumcision on a U.S. male's lifetime risk of HIV, including associated costs and quality-adjusted life-years saved. METHODOLOGY/PRINCIPAL FINDINGS: Given published estimates of U.S. males' lifetime HIV risk, we calculated the fraction of lifetime risk attributable to heterosexual behavior from 2005-2006 HIV surveillance data. We assumed 60% efficacy of circumcision in reducing heterosexually-acquired HIV over a lifetime, and varied efficacy in sensitivity analyses. We calculated differences in lifetime HIV risk, expected HIV treatment costs and quality-adjusted life years (QALYs) among circumcised versus uncircumcised males. The main outcome measure was cost per HIV-related QALY saved. Circumcision reduced the lifetime HIV risk among all males by 15.7% in the base case analysis, ranging from 7.9% for white males to 20.9% for black males. Newborn circumcision was a cost-saving HIV prevention intervention for all, black and Hispanic males. The net cost of newborn circumcision per QALY saved was $87,792 for white males. Results were most sensitive to the discount rate, and circumcision efficacy and cost. CONCLUSIONS/SIGNIFICANCE: Newborn circumcision resulted in lower expected HIV-related treatment costs and a slight increase in QALYs. It reduced the 1.87% lifetime risk of HIV among all males by about 16%. The effect varied substantially by race and ethnicity. Racial and ethnic groups who could benefit the most from circumcision may have least access to it due to insurance coverage and state Medicaid policies, and these financial barriers should be addressed. More data on the long-term protective effect of circumcision on heterosexual males as well as on its efficacy in preventing HIV among MSM would be useful

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 [1] and was estimated at 48,600 cases in 2006 and 48,100 in 2009 [2]. 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

Recommendations for increasing the use of HIV/AIDS resource allocation models

The article of record as published may be found at: http://dx.doi.org/10.1186/1471-2458-9-S1-S8Background: Resource allocation models have not had a substantial impact on HIV/AIDS resource allocation decisions in spite of the important, additional insights they may provide. In this paper, we highlight six difficulties often encountered in attempts to implement such models in policy settings; these are: model complexity, data requirements, multiple stakeholders, funding issues, and political and ethical considerations. We then make recommendations as to how each of these difficulties may be overcome. Results: To ensure that models can inform the actual decision, modellers should understand the environment in which decision-makers operate, including full knowledge of the stakeholders' key issues and requirements. HIV/AIDS resource allocation model formulations should be contextualized and sensitive to societal concerns and decision-makers' realities. Modellers should provide the required education and training materials in order for decision-makers to be reasonably well versed in understanding the capabilities, power and limitations of the model. Conclusion: This paper addresses the issue of knowledge translation from the established resource allocation modelling expertise in the academic realm to that of policymaking

A model for allocating CDC’s HIV prevention resources in the United States

HIV/AIDS, Resource allocation, Optimization model,

Estimating the Impact of State Budget Cuts and Redirection of Prevention Resources on the HIV Epidemic in 59 California Local Health Departments

<div><p>Background</p><p>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.</p> <p>Methods and Findings</p><p>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.</p> <p>Conclusions</p><p>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.</p> </div

Public health modeling at the Centers for Disease Control and Prevention

At the Centers for Disease Control and Prevention, there is a growing interest in promoting the use of mathematical modeling to support public health policies. This chapter presents three examples of operations research models developed and employed by the Centers for Disease Control and Prevention. First, we discuss the Adult Immunization Scheduler, which uses dynamic programming methods to establish a personalized vaccination schedule for adults aged 19 and older. The second operations research project is a discrete event simulation model used to estimate the throughput and budget for mass vaccination clinics during the 2009-2010 H1N1 pandemic. Lastly, we describe a national HIV resource allocation model that uses nonlinear programming methods to optimize the allocation of funds to HIV prevention programs and populations

Cost implications of HIV retesting for verification in Africa.

INTRODUCTION:HIV misdiagnosis leads to severe individual and public health consequences. Retesting for verification of all HIV-positive cases prior to antiretroviral therapy initiation can reduce HIV misdiagnosis, yet this practice has not been not widely implemented. METHODS:We evaluated and compared the cost of retesting for verification of HIV seropositivity (retesting) to the cost of antiretroviral treatment (ART) for misdiagnosed cases in the absence of retesting (no retesting), from the perspective of the health care system. We estimated the number of misdiagnosed cases based on a review of misdiagnosis rates, and the number of positives persons needing ART initiation by 2020. We presented the total and per person costs of retesting as compared to no retesting, over a ten-year horizon, across 50 countries in Africa grouped by income level. We conducted univariate sensitivity analysis on all model input parameters, and threshold analysis to evaluate the parameter values where the total costs of retesting and the costs no retesting are equivalent. Cost data were adjusted to 2017 United States Dollars. RESULTS AND DISCUSSION:The estimated number of misdiagnoses, in the absence of retesting was 156,117, 52,720 and 29,884 for lower-income countries (LICs), lower-middle income countries (LMICs), and upper middle-income countries (UMICs), respectively, totaling 240,463 for Africa. Under the retesting scenario, costs per person initially diagnosed were: $40,$21, and $42, for LICs, LMICs, and UMICs, respectively. When retesting for verification is implemented, the savings in unnecessary ART were$125, $43, and$75 per person initially diagnosed, for LICs, LMICs, and UMICs, respectively. Over the ten-year horizon, the total costs under the retesting scenario, over all country income levels, was $475 million, and was$1.192 billion under the no retesting scenario, representing total estimated savings of $717 million in HIV treatment costs averted. CONCLUSIONS:Results show that to reduce HIV misdiagnosis, countries in Africa should implement the WHO's recommendation of retesting for verification prior to ART initiation, as part of a comprehensive quality assurance program for HIV testing services