Statistical Methods for Advancing HIV Prevention

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Project Summary/Abstract Antiretroviral-based HIV prophylaxis is highly effective at preventing acquisition of HIV, yet there are many implementation challenges. Population-based effectiveness studies seek to evaluate real-world impact of preventive interventions. There is, however, a major limitation in our current ability to measure effectiveness of preventive interventions at the population-level due to its requirement of resource-extensive longitudinal testing in a closed cohort. HIV recency assays (assays that provide information on the timing of HIV acquisition) offer resource- efficient estimates of incidence. However, the utility of such assays is currently limited due to lack of precision. In addition, designing efficacy trials to evaluate new HIV preventive interventions is increasingly challenging when effective prevention agents exist. To fill these gaps, we will advance statistical methodology to measure HIV incidence and develop a new trial design to assess efficacy of an HIV preventive intervention. Specifically, we will extend existing methods for estimating HIV incidence using recency assay data to accommodate covariate effects on assay properties, temporal trends in HIV incidence, and to estimate HIV incidence with increased precision. We will also develop a new class of HIV prevention efficacy trial design termed the ‘augmented active-controlled design’ which will leverage additional information to infer HIV incidence absent intervention, i.e. ‘counterfactual placebo’ HIV incidence. To extend and develop these methods, we will define a statistical framework; define approaches to estimating and drawing inference about parameters given the data; derive and compare analytic properties of the inferential methods; evaluate performance in simulation studies; and apply the methods to real data to generate new scientific insights. These novel methods have direct application to evaluating the impact of HIV preventive interventions in population-based effectiveness studies and randomized controlled efficacy trials, and will be applicable to the study of other infectious diseases. 1