IMPACT OF ANTIRETROVIRAL PREVENTION ON EMERGENCE AND SPREAD OF HIV DRUG RESISTA

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The potential impact of antiretroviral pre-exposure prophylaxis on the development and heterosexual transmission of human immunodeficiency virus (HIV) drug resistance is unknown and has not been modeled. This project will investigate the effect of antiretroviral chemoprophylaxis on the epidemiologic patterns of HIV drug resistance using a new generation of mathematical and computational models that represent realistic biological, demographic, epidemiologic and behavioral heterogeneities that underlie the dynamics of HIV drug resistance. These innovative models: i) incorporate variation in plasma viremia, CD4 cell decline, HIV disease progression, infectiousness, risk behavior, and effect of antiretroviral chemoprophylaxis both within and among individuals; ii) simulate different strategies of chemoprophylaxis use; and iii) predict HIV drug resistance outcomes at the population level. Our long term goal is to use modeling and simulation to design public health intervention strategies that will help control the global HIV epidemic. The central hypothesis is that targeting specific subpopulations of persons at highest risk for transmitting and acquiring HIV infection can minimize the spread of HIV drug resistance. The specific aims proposed are: i) to simulate an HIV epidemic under different scenarios of antiretroviral chemoprophylaxis implementation and analyze the predicted patterns of HIV drug resistance; ii) to identify the key determinants of the predicted patterns of HIV drug resistance and evaluate the prediction uncertainty; and iii) to determine the sensitivity of the model predictions to modeling framework and assumptions. The proposed research is novel in that multiple modeling approaches and modeling scales will be used to simulate the effect of different antiretroviral chemoprophylaxis strategies on the incidence and prevalence of HIV drug resistance in resource-limited settings. Our findings should help identify the key determinants for spread of HIV drug resistance and the most effective antiretroviral chemoprophylaxis strategies to curb both the global HIV epidemic and drug resistance.