Optimizing HIV Treatment in Resource-Limited Settings Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/js956j46q

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  • Apart from the traditional role of preventing progression from HIV to AIDS, antiretroviral drug therapy (ART) has an additional benefit of substantially reducing infectiousness, making them potentially an important strategy in the fight against HIV. Recent advances in drug therapy have also seen the use of antiretroviral drugs as a prophylaxis, administered either as post-exposure prophylaxis (PEP) after high-risk exposure or as pre-exposure prophylaxis (PrEP) in those with ongoing HIV exposure. In this dissertation I developed two models for HIV transmission and parameterized them with data from South Africa to study governmental-level intervention programs in which antiretroviral drugs are given as treatment and prophylaxis. The first model is based on the dynamics of HIV in heterosexual population in Sub- Saharan Africa. The model classifies the male and female adult populations by HIV risk into three categories (low, medium and high) according to their sexual preferences. I used a non-linear optimization method to determine the optimal population-level allocation of ART and PrEP allocations required to minimize four objectives: new infections, infection-years, deaths and cost. I considered several strategies for allocating ART and PrEP. I found that generally for low treatment availability, prevention through PrEP to the general population or PrEP and ART to high-risk females is key to optimize all objectives, while for higher drug availability, an all-ART treatment is optimal. At South Africa’s current level of treatment availability, using prevention is most effective at reducing new infections, infection-years, and cost, while using the treatment as ART to the general population best reduces deaths. At treatment levels that meet the UNAIDS's ambitious new 90-90-90 target in South Africa, using all or almost all treatment as ART to the general population best reduces all four objectives considered. The second model is based on the WHO's five-stage classification of HIV/AIDS disease progression. This models stratified the population by disease status, whether diagnosed and whether on treatment. I used optimal control methods to determine the best time-dependent treatment allocation required to minimize new infections, infection-years, deaths and cost. My results indicated that the treatment strategy to minimize infection-years and new infections is to place emphasis on early treatment (i.e. treatment in Stage II & III) while to minimize cost and death, the emphasis should be on late treatment (i.e. Stage III & IV). Applying the optimal treatment strategy also leads to a substantial reduction in disease incidence and prevalence. The results of this study will hopefully provides some guidance for policymakers in determining how to allocate antiretroviral drugs in order to maximize the benefit of treatment.
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