Abstract
INTRODUCTION: Oral pre-exposure prophylaxis (PrEP) is a new form of HIV prevention being considered for inclusion in national prevention portfolios. Many mathematical modelling studies have been undertaken that speak to the impact, cost and cost-effectiveness of PrEP programmes. We assess the available evidence from mathematical modelling studies to inform programme planning and policy decision making for PrEP and further research directions. METHODS: We conducted a scoping review of the published modelling literature. Articles published in English which modelled oral PrEP in sub-Saharan Africa, or non-specific settings with relevance to generalized HIV epidemic settings, were included. Data were extracted for the strategies of PrEP use modelled, and the impact, cost and cost-effectiveness of PrEP for each strategy. We define an algorithm to assess the quality and relevance of studies included, summarize the available evidence and identify the current gaps in modelling. Recommendations are generated for future modelling applications and data collection. RESULTS AND DISCUSSION: We reviewed 1924 abstracts and included 44 studies spanning 2007 to 2017. Modelling has reported that PrEP can be a cost-effective addition to HIV prevention portfolios for some use cases, but also that it would not be cost-effective to fund PrEP before other prevention interventions are expanded. However, our assessment of the quality of the modelling indicates cost-effectiveness analyses failed to comply with standards of reporting for economic evaluations and the assessment of relevance highlighted that both key parameters and scenarios are now outdated. Current evidence gaps include modelling to inform service development using updated programmatic information and ex post modelling to evaluate and inform efficient deployment of resources in support of PrEP, especially among key populations, using direct evidence of cost, adherence and uptake patterns. CONCLUSIONS: Updated modelling which more appropriately captures PrEP programme delivery, uses current intervention scenarios, and is parameterized with data from demonstration and implementation projects is needed in support of more conclusive findings and actionable recommendations for programmes and policy. Future analyses should address these issues, aligning with countries to support the needs of programme planners and decision makers for models to more directly inform programme planning and policy.