Phylodynamic analysis of HIV sub-epidemics in Mochudi, Botswana
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CitationNovitsky, Vlad, Denise Kühnert, Sikhulile Moyo, Erik Widenfelt, Lillian Okui, and M. Essex. 2015. “Phylodynamic Analysis of HIV Sub-Epidemics in Mochudi, Botswana.” Epidemics 13 (December): 44–55. doi:10.1016/j.epidem.2015.07.002.
AbstractSouthern Africa continues to be the epicenter of the HIV/AIDS epidemic. This HIV-1 subtype C epidemic has a predominantly heterosexual mode of virus transmission and high (>15%) HIV prevalence among adults. The epidemiological dynamics of the HIV-1C epidemic in southern Africa are still poorly understood. Here, we aim at a better understanding of HIV transmission dynamics by analyzing HIV-1 subtype C sequences from Mochudi, a peri-urban village in Botswana. HIV-1C env gene sequences (gp120 V1C5) were obtained through enhanced household-based HIV testing and counseling in Mochudi. More than 1200 sequences were generated and phylogenetically distinct sub-epidemics within Mochudi identified. The Bayesian birth-death skyline plot was used to estimate the effective reproductive number, R, and the timing of virus transmission, to classify sub-epidemics as "acute" (those with recent viral transmissions) or "historic" (those without recent viral transmissions). We identified two of the 15 sub-epidemics as "acute." The median estimates of R among the clusters ranged from 0.72 to 1.77. The majority of HIV lineages, 11 out of 15 clusters with 5+ members, appear to have been introduced to Mochudi between 1996 and 2002. The median peak duration of viral transmissions was 7.1 years (range 2.9-9.7 years). The median life span of identified HIV sub-epidemics, i.e., the time between the inferred epidemic origin and its most recent sample, was 13.1 years (range 10.2-22.1 years). Most viral transmissions within the sub-epidemics occurred between 1997 and 2007. The time period during which infected people are infectious appears to have decreased since the introduction of the national ART program in Botswana. Real-time HIV genotyping and breaking down local HIV epidemics into phylogenetically distinct sub-epidemics may help to reveal the structure and dynamics of HIV transmission networks in communities, and aid in the design of targeted interventions for members of the acute sub-epidemics that likely fuel local HIV/AIDS epidemics.
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