A decision analytics model to optimize investment in interventions targeting the HIV preexposure prophylaxis cascade of care

Abstract

OBJECTIVES: Gaps between recommended and actual levels of HIV preexposure prophylaxis (PrEP) use remain among MSM. Interventions can address these gaps but it is unknown how public health initiatives should invest prevention funds into these interventions to maximize their population impact. DESIGN: We used a stochastic network-based HIV transmission model for MSM in the Atlanta area paired with an economic budget optimization model. METHODS: The model simulated MSM participating in up to three real-world PrEP cascade interventions designed to improve initiation, adherence, or persistence. The primary outcome was infections averted over 10 years. The budget optimization model identified the investment combination under different budgets that maximized this outcome, given intervention costs from a payer perspective. RESULTS: From the base 15% PrEP coverage level, the three interventions could increase coverage to 27%, resulting in 12.3% of infections averted over 10 years. Uptake of each intervention was interdependent: maximal use of the adherence and persistence interventions depended on new PrEP users generated by the initiation intervention. As the budget increased, optimal investment involved a mixture of the initiation and persistence interventions but not the adherence intervention. If adherence intervention costs were halved, the optimal investment was roughly equal across interventions. CONCLUSION: Investments into the PrEP cascade through initiatives should account for the interactions of the interventions as they are collectively deployed. Given current intervention efficacy estimates, the total population impact of each intervention may be improved with greater total budgets or reduced intervention costs.