A Markov Model Examining Intervention Effects on the HIV Prevalence/Incidence amongst the Overall Population

Abstract Human Immunodeficiency Virus (HIV) remains a high burden in Africa. Several targeted prevention strategies are prevalent including the promotion of condom use, provision of anti-retroviral therapy (ART) and pre-exposure prophylaxis (PrEP). Optimal allocation of limited resources requires understanding how the HIV epidemic will be affected by these strategies. We develop a Markov model, considering three populations: female sex workers (FSWs), general population (GP) and sex clients (SCs), which estimates the effects of these strategies on the HIV prevalence/incidence in Rwanda from 2017 to 2027. Using Rwanda’s demographic, sexual risk behavior, and HIV-associated morbidity/mortality data, it was determined that by 2027 , a 30 % improvement in consistent condom use amongst female sex workers would reduce the HIV prevalence amongst female sex workers, sex clients, and the general population by 7.86 % , 5.97 % , and 0.17 % , respectively. Secondly, while making improvements on the recurrent HIV testing as well as ART coverage only mildly reduces the prevalence/incidence amongst female sex workers, and sex clients, reducing the two would result in an increase in the HIV prevalence/incidence amongst FSWs and SCs. Lastly, our analysis shows that introduction of PrEP to female sex workers in 2019 is expected to reduce the HIV incidence amongst FSWs by 1.28 % over the next decade. We further analyze scaling-up PrEP beyond the highest-risk population, i.e., FSWs, and weigh population-level impact with cost-effectiveness to make an informed priority-setting amongst women in the general population. We modeled the HIV risk to women, and computed the impact, cost, and cost-effectiveness of PrEP scale-up for younger women aged 15 − 25 , women aged 25 − 34 , and women aged 35 − 49 years, while accounting for the low program retention levels reported in demonstration projects. Perhaps, counter-intuitively, it is shown that PrEP could substantially avert more infections a year amongst women in the general population than amongst female sex workers. In summary, our models and analysis could help decision makers effectively allocate resources to each of these prevention/treatment strategies amongst different sub-populations.