Unpacking sources of transmission in HIV prevention trials with deep-sequence pathogen data

Abstract

Abstract To develop effective HIV prevention strategies to guide public health policy the main sources of infection in HIV prevention studies must be identified. Accordingly, we devised a statistical approach that estimates the relative contribution of different sources of infection in community-randomized trials of infectious disease prevention using deep- (or next generation) sequenced pathogen data. We applied this approach to the Botswana Combination Prevention Project (BCPP) and estimated that 90% [95% Confidence Interval (CI): 80–94] of new infections in communities that received combination prevention (including universal HIV test-and-treat) originated from individuals residing in communities outside the trial area. We estimate from our model that the relative benefit of providing the BCPP intervention to all communities nationwide would be a 59% [3–87] reduction in transmissions to recipients in trial communities, exceeding the 30% reduction observed when providing the BCPP intervention to trial communities only. Our results suggest that the impact of the BCPP trial intervention was curtailed by sources of transmission outside the trial area and could be considerably larger if applied nationally. We recommend that the impact of sources of transmission beyond the reach of the intervention be considered when designing and evaluating interventions to inform public health programs.