Phylodynamic analysis of HIV-1 subtypes B, C and CRF 02_AG in Senegal

Abstract

Surveillance of HIV epidemics in key populations and in developing countries is often challenging due to sparse, incomplete, or low-quality data. Analysis of HIV sequence data can provide an alternative source of information about epidemic history, population structure, and transmission patterns. To understand HIV-1 dynamics and transmission patterns in Senegal, we carried out model-based phylodynamic analyses using the structured-coalescent approach using HIV-1 sequence data from three different subgroups: reproductive aged males and females from the adult Senegalese population and men who have sex with other men (MSM). We fitted these phylodynamic analyses to time-scaled phylogenetic trees individually for subtypes C and CRF 02_AG, and for the combined data for subtypes B, C and CRF 02_AG. In general, the combined analysis showed a decreasing proportion of effective number of infections among all reproductive aged adults relative to MSM. However, we observed a nearly time-invariant distribution for subtype CRF 02_AG and an increasing trend for subtype C on the proportion of effective number of infections. The population attributable fraction also differed between analyses: subtype CRF 02_AG showed little contribution from MSM, while for subtype C and combined analyses this contribution was much higher. Despite observed differences, results suggested that the combination of high assortativity among MSM and the unmet HIV prevention and treatment needs represent a significant component of the HIV epidemic in Senegal.

Keywords: Coalescent; HIV; Key populations; Phylodynamics.

Fig. 1.

Effective number/proportion of infections in risk groups for subtype CRF 02_AG. Plots showing the absolute number and proportion of the effective number of infections in each deme/group (gpf, gpm and msm) for the individual analyses for subtype CRF 02_AG. Shaded area represents the 95% credible interval. MAP = maximum a posteriori.

Fig. 2.

Effective number/proportion of infections in risk groups for subtype C. Plots showing the absolute number and proportion of the effective number of infections in each deme/group (gpf, gpm and msm) for the individual analyses for subtype C. Shaded area represents the 95% credible interval. MAP = maximum a posteriori.

Fig. 3.

Effective number/proportion of infections in risk groups for the combined analyses. Plots showing the absolute number and proportion of the effective number of infections in each deme/group (gpf, gpm and msm) for the combined analyses (including subtypes B, C and CRF 02_AG). Shaded area represents the 95% credible interval. The y-axis for proportion of infections in msm is the same as for gp. MAP = maximum a posteriori.

Fig. 4.

Population attributable fraction. Plots showing the population attributable fraction for each deme/group (gpf, gpm and msm) for the individual analyses for subtypes C and 02_AG, and for the combined analyses (including subtypes B, C and 02_AG). Point estimates and error bars in the last plot represents 1-year PAF estimated for MSM in Mukandavire et al. (2018). Shaded area represents the 95% credible interval. When not shown, y-axis is horizontally shared between plots. MAP =maximum a posteriori.

Fig. 5.

Sensitivity analyses. Plots showing the population attributable fraction for msm for the combined analyses (including subtypes B, C and 02_AG). Point estimates and error bars represent 1-year MSM PAF estimated in Mukandavire et al. (2018) for 1995, 2005 and 2015. Shaded area represents the 95% credible interval. MAP = maximum a posteriori.