Full TitleFIND-PrEP - Finding the optimal distribution of pre-exposure prophylaxis of HIV among sex workers, a computational modeling approach
Female sex workers are vulnerable to HIV, and particularly so in resource-constrained countries. Improving prevention of HIV among them is crucial to reduce its burden on the welfare of those populations, and also a crucial step towards UNAIDS’ goal of ending the HIV/AIDS epidemic by 2030. Pre-Exposure Prophylaxis (PrEP) is the use of antiretrovirals medications to protect people from HIV infection, even during unprotected sex. Building on our previous findings, we will develop a mathematical and computational model to evaluate the performance, in terms of averted infections, of competing PrEP distribution strategies among female sex workers. We will identify the best-performing strategy for different scenarios spanning communities in different countries, in terms of HIV prevalence, access to treatment, prevention-related behavior, and prevalence of other sexually transmitted diseases, which, by changing susceptibility to HIV, may alter the overall effectiveness of PrEP distribution.