Unpacking sources of transmission in HIV prevention trials with deep-sequence pathogen data – BCPP/ Ya Tsie study

Abstract

AbstractTo develop effective HIV prevention strategies that can guide public health policy it is important to identify the main sources of infection in HIV prevention studies. Accordingly, we devised a statistical approach that leverages deep- (or next generation) sequenced pathogen data to estimate the relative contribution of different sources of infection in community-randomized trials of infectious disease prevention. We applied this approach to the Botswana Combination Prevention Project (BCPP) and estimated that 90% [95% Confidence Interval (CI): 81 – 93] of new infections that occurred in individuals in communities that received combination prevention (including universal HIV test-and-treat) originated from individuals residing in communities outside of the trial area. We estimate that the relative impact of the intervention was greater in rural geographically isolated communities with limited opportunity for imported infections compared to communities neighboring major urban centers. Treating people with HIV limits the spread of infection to uninfected individuals; accordingly, counterfactual modeling scenarios estimated that a nationwide application of the intervention could have reduced transmissions to recipients in trial communities by 59% [3 – 87], much higher than the observed 30% reduction. Our results suggest that the impact of the BCPP trial intervention was substantially limited by sources of transmission outside the trial area, and that the impact of the intervention could be considerably larger if applied nationally. We recommend that studies of infectious disease prevention consider the impact of sources of transmission beyond the reach of the intervention when designing and evaluating interventions to inform public health programs.