Epidemics (Dec 2015)

Phylodynamic analysis of HIV sub-epidemics in Mochudi, Botswana

  • Vlad Novitsky,
  • Denise Kühnert,
  • Sikhulile Moyo,
  • Erik Widenfelt,
  • Lillian Okui,
  • M. Essex

DOI
https://doi.org/10.1016/j.epidem.2015.07.002
Journal volume & issue
Vol. 13, no. C
pp. 44 – 55

Abstract

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Southern 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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