HIV - Emergence of Drug Resistance

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DESCRIPTION (provided by applicant): This application is in response to NOT-OD-10-033, "NIH Announces the Availability of Recovery Act Funds for Competitive Revision Applications (RO1, RO3, R15, R21, R21/R33, and R37) for HIV/AIDS-related Research through the NIH Basic Behavioral and Social Science Opportunity Network (OppNet)." The work of the parent award focuses on combining mathematical modeling with statistical analysis of datasets to predict the evolution of drug-resistant strains of HIV in the US, Europe, and Africa. In the revision our work will be extended by developing detailed risk maps for HIV infection that are spatially-explicit and based on data from Botswana. We aim to (i) develop detailed data-based spatial risk maps of Botswana which will identify individuals (based on gender and age) that are most at risk of infection and where they are geographically located throughout the country and (ii) use these risk maps and individual- based stochastic simulation modeling to evaluate the potential consequences of Pre-Exposure Prophylaxis (PrEP) interventions on decreasing transmission and increasing drug-resistance in Botswana. In addition we will use optimal control theory to design an implementation plan that will maximize the effectiveness of PrEP in preventing infections and minimize the effect of PrEP on increasing resistance. We will predict the potential impact of PrEP interventions on increasing the need for second-line therapies in both the short-term and long- term. The research we are proposing builds upon our past two decades of research on modeling HIV and other infectious diseases, but takes our HIV research in new directions by: (i) constructing spatial risk maps for HIV based on gender, age and geography, (ii) using spatial statistics to identify "hot-spots" of risk for acquiring HIV, (iii) building detailed data-based high resolution models using individual-based simulation modeling, (iv) designing a country-specific model for Botswana focusing on the geographic heterogeneity of the HIV epidemic throughout the country and (v) using optimization techniques to design HIV interventions based on PrEP. Our proposed new research involves collaborations with the International Partnership for Microbicides, the Center for Disease Control and Prevention (CDC) and the African Comprehensive HIV and AIDS Program (ACHAP). ACHAP is a non-profit organization that links the Government of Botswana with the Bill and Melinda Gates Foundation. We aim to design optimal rollout plans for interventions based on PrEP in Botswana using data obtained from our collaborators in Botswana and virologic data on PrEP obtained from our collaborators at the CDC. By constructing detailed spatially-explicit models and employing optimization techniques we will be able to identify how to maximize the effectiveness of PrEP interventions and to identify the optimal geographic locations where the rollout should begin. PUBLIC HEALTH RELEVANCE: The control of the HIV pandemic is a global problem that has yet to be solved. Our overall objective is to develop detailed spatially-explicit data-based HIV transmission models for Botswana and to use these models to design optimal interventions for preventing HIV infections. Our results will have direct relevance for health policy makers and Governments in resource-constrained countries, as well as for other scientists.