Background: The rapid intrinsic evolution of HIV-1 makes it possible to infer epidemiologic patterns from sequence data. The Bayesian birth-death skyline (BDSKY) plot was introduced recently as a model of virus transmission. We used BDSKY to estimate the effective reproductive number, R, and the timing of virus transmission, to distinguish “acute” HIV sub-epidemics (with recent viral transmissions) from “historic” sub-epidemics (without recent viral transmissions) in a southern-African community.
Methods: Study subjects participated in enhanced household-based HIV Testing and Counselling in Mochudi, a peri-urban village in Botswana. The sampling density was around 70%. HIV-1C V1C5 sequences were generated for 1,248 residents of Mochudi. HIV-1C sub-epidemics were identified by a combination of bootstrapped maximum likelihood and internode certainty. For HIV sub-epidemics with 5+ members, the epidemiological parameters were inferred from virus sequence data. The time line for each sub-epidemic was estimated by fitting the BDSKY model and inferring the tree height and internal node ages in the Maximum Clade Credibility time-trees using BEAST2. For each sub-epidemic we estimated the time interval the majority of HIV transmissions occurred in, with corresponding 95% HPD intervals.
Results: We employed the BDSKY model to estimate effective reproductive number R and timing of HIV-1C transmissions within 15 sub-epidemics with 5+ members. Only three of the 15 sub-epidemics were estimated as “acute” with recent HIV transmissions. The median estimates of R were 0.7–1.6. The V1C5-based informativeness of R estimates differed across sub-epidemics. The median peak duration of viral transmissions was 5.4 years (95% HPD, 3.8 to 8.6 years). The median life span of identified HIV sub-epidemics, i.e., the time from the cluster’s origin to its most recent sample, was 14.2 years (95% HPD, 9.8 to 16.4 years). The majority of viral transmissions within 15 identified HIV sub-epidemics in Mochudi occurred between 1997 and 2005. The generated data suggests that the time period during which infected people are infectious has decreased significantly since the introduction of ART in Botswana as the national program.
Conclusions: Viral sequence data from a densely sampled community in Botswana allowed us to estimate the effective reproductive number, R, and timing of virus transmissions in 15 local HIV sub-epidemics. “Acute” sub-epidemics with recent HIV transmissions are likely to fuel local HIV/AIDS epidemics.