Mathematical models to inform effective home-use HIV testing strategies for MSM

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 DESCRIPTION (provided by applicant): The U.S. Food and Drug Administration (FDA) approved the first over-the-counter home-use HIV test in 2012. Public health departments have started to implement programs to increase their use; however, the potential impact of these tests on the HIV epidemic among men who have sex with men (MSM) is unknown. The aim of this research is to inform public health approaches to promote safe and effective home-use HIV testing strategies for diverse populations of MSM. Home-use HIV tests may reduce HIV incidence if used by MSM who would otherwise not test or if they increase rates of testing, diagnosis and treatment. However, home-use tests may increase transmission if men replace clinic-based tests with home-use tests because the relatively long window period of available tests can result in false-negative tests during acute infection when HIV-infected persons are most infectious. Home-use tests may also negatively impact the infected individual's health and pose a challenge for HIV prevention if men who test positive at home do not seek care and initiate antiretroviral therapy (ART) in a timely manner. Men may use home-use tests with sex partners prior to sex to make decisions about whether and how to have sex [5]. Such point-of-sex testing may be beneficial if partners test more often and seroadapt based on more accurate information but may increase HIV risk if men forgo condoms based on incorrect information about serostatus. Using data from two different epidemiologic settings in the U.S., Seattle and Atlanta, we will use mathematical models to estimate how different strategies of home-use HIV testing at the individual and partnership levels affects HIV incidence. First, we will develop a se of parameters to represent novel and heterogeneous HIV testing strategies for MSM, and adapt, expand, and validate a stochastic network-based HIV transmission model to account for home-use testing strategies and seroadaptive behavior for MSM in Seattle, WA and Atlanta, GA. Second, we will use the models to identify the most effective individual home-use HIV testing strategies to increase awareness of HIV infection and reduce HIV incidence among MSM in the two settings. Third, we will predict the impact of home-use point-of-sex HIV testing strategies on dyadic-level awareness of HIV infection and HIV incidence among MSM in Seattle versus Atlanta. In this proposal, our models are akin to a virtual laboratory: a practical and cost-effective way to examine the scenarios under which home-use testing can effectively reduce HIV incidence in diverse high-risk populations. Moreover, our models can support the design of clinical trials to test the effectiveness of home-use HIV testing interventions if such an initiatie is warranted.