Estimating the contribution of key populations towards HIV transmission in South Africa

Abstract

Introduction: In generalized epidemic settings, there is insufficient understanding of how the unmet HIV prevention and treatment needs of key populations (KPs), such as female sex workers (FSWs) and men who have sex with men (MSM), contribute to HIV transmission. In such settings, it is typically assumed that HIV transmission is driven by the general population. We estimated the contribution of commercial sex, sex between men, and other heterosexual partnerships to HIV transmission in South Africa (SA).

Methods: We developed the "Key-Pop Model"; a dynamic transmission model of HIV among FSWs, their clients, MSM, and the broader population in SA. The model was parameterized and calibrated using demographic, behavioural and epidemiological data from national household surveys and KP surveys. We estimated the contribution of commercial sex, sex between men and sex among heterosexual partnerships of different sub-groups to HIV transmission over 2010 to 2019. We also estimated the efficiency (HIV infections averted per person-year of intervention) and prevented fraction (% IA) over 10-years from scaling-up ART (to 81% coverage) in different sub-populations from 2020.

Results: Sex between FSWs and their paying clients, and between clients with their non-paying partners contributed 6.9% (95% credibility interval 4.5% to 9.3%) and 41.9% (35.1% to 53.2%) of new HIV infections in SA over 2010 to 2019 respectively. Sex between low-risk groups contributed 59.7% (47.6% to 68.5%), sex between men contributed 5.3% (2.3% to 14.1%) and sex between MSM and their female partners contributed 3.7% (1.6% to 9.8%). Going forward, the largest population-level impact on HIV transmission can be achieved from scaling up ART to clients of FSWs (% IA = 18.2% (14.0% to 24.4%) or low-risk individuals (% IA = 20.6% (14.7 to 27.5) over 2020 to 2030), with ART scale-up among KPs being most efficient.

Conclusions: Clients of FSWs play a fundamental role in HIV transmission in SA. Addressing the HIV prevention and treatment needs of KPs in generalized HIV epidemics is central to a comprehensive HIV response.

Keywords: clients; female sex workers; key populations; mathematical modelling; men who have sex with men; population attributable fraction.

Figure 1

Model schematics illustrating the (a) movement of individuals in and out of different sub‐populations (b) sexual interactions which can result in HIV transmission among low‐risk females, low‐risk males, female sex workers, their clients and men who have sex with men and (c) stratification of the population with respect to HIV infection. Red dashed arrow in (b) denotes commercial sex and all other arrows denote sex with main and casual partners. Note that non‐related HIV mortality not shown in (c) for clarity. LTFU denotes loss to ART care; FSW denotes female sex workers; MSM denotes men who have sex with men.

Figure 2

Estimated condom use trends for (a) commercial sex (vaginal intercourse ‐ VI) for female sex workers (FSW) and (b) male main and casual partners of men who have sex with men (MSM). For commercial sex, we assume condom use for anal intercourse is 0.5 to 1 times that of vaginal intercourse for all years. Continuous black line indicates median projections from all the baseline model fits with shaded areas showing 95% CrI. Vertical black lines show prior ranges.

Figure 3

A comparison of median and 95% credibility intervals from baseline model fits (black line and shaded area) with HIV prevalence estimates for (a) overall adult population, (b) adult male and (c) adult female general population, (d) female sex workers (FSWs), (e) their clients, and (f) men who have sex with men (MSM) and HIV prevalence projections without ART (green line), without scale‐up in male circumcision (orange line) and without condom use (blue line). Red points and whiskers show data with 95% confidence intervals used for model calibration, and black points show cross validation data not used in model calibration but shown to compare with model projections.

Figure 4

A comparison of median and 95% credibility intervals from baseline model fits (black line and shaded area) with HIV incidence estimates for (a) overall adult population, (b) adult male and (c) adult female general population, (d) female sex workers (FSWs), (e) their clients, and (f) men who have sex with men (MSM) and HIV incidence projections without ART (green line), without scale‐up in male circumcision (orange line) and without condom use (blue line). Black points show cross validation data not used in model calibration but shown to validate the model projections. Note that the scale for the y‐axes are different for panels (d) and (f).

Figure 5

Ten and thirty‐year transmission population attributable fraction (tPAF) for different sexual partnership types. The tPAF is estimated as the proportion of all HIV infections prevented if the HIV transmission risk due to a specific type of sexual behaviour is removed over the following time periods: 1990 to 2019, 2010 to 2019 and 2020 to 2029. The box plots signify the uncertainty (middle line is median, limits of boxes are the 25% and 75% percentiles, and whiskers are 2.5% and 97.5% percentile range) in the tPAF estimates due to uncertainty in the model parameters. FSW, female sex workers; MSM, men who have sex with men.

Figure 6

The prevented fraction and efficiency of scaling‐up ART coverage to 81% (UNAIDS 90:90:90 target) within each sub‐group from 2020 to 2030. (a) shows the impact of targeting treatment to each sub‐group measured as the prevented fraction (% of new HIV infections that could be averted) over 2020 to 2030. (b) Shows the efficiency of targeting treatment to each sub‐group, measured as the number of infections averted per 100 py of intervention. The box plots signify the uncertainty (middle line is median, limits of boxes are the 25% and 75% percentiles, and whiskers are 2.5% and 97.5% percentile range) in the impact projections due to uncertainty in the baseline model fits. FSW, female sex workers; MSM, men who have sex with men.