Temporal change in population-level prevalence of detectable HIV viraemia and its association with HIV incidence in key populations in India: a serial cross-sectional study

Abstract

Background: Population-level prevalence of detectable HIV viraemia (PDV) has been proposed as a metric for monitoring the population-level effectiveness of HIV treatment as prevention. We aimed to characterise temporal changes in PDV in people who inject drugs (PWID) and men who have sex with men (MSM) in India and evaluate community-level and individual-level associations with cross-sectional HIV incidence.

Methods: We did a serial cross-sectional study in which baseline (from Oct 1, 2012, to Dec 19, 2013) and follow-up (from Aug 1, 2016, to May 28, 2017) respondent-driven sampling (RDS) surveys were done in MSM (ten community sites) and PWID (12 community sites) across 21 cities in India. Eligible participants were those aged 18 years or older who provided informed consent and possessed a valid RDS referral coupon. Annualised HIV incidence was estimated with validated multiple-assay algorithms. PDV was calculated as the percentage of people with detectable HIV RNA (>150 copies per mL) in a community site. Community-level associations were determined by linear regression. Multivariable, multilevel Poisson regression was used to assess associations with recent HIV infection.

Findings: We recruited 21 990 individuals in the baseline survey and 21 726 individuals in the follow-up survey. The median community-level HIV incidence estimate increased from 0·9% (range 0·0-2·2) at baseline to 1·5% (0·5-3·0) at follow-up in MSM and from 1·6% (0·5-12·4) to 3·6% (0·0-18·4) in PWID. At the community-level, every 1 percentage point increase in baseline PDV and temporal change in PDV between surveys was associated with higher annualised HIV incidence at follow-up: for baseline PDV β=0·41 (95% CI 0·18-0·63) and for change in PDV β=0·52 (0·38-0·66). After accounting for individual-level risk factors, every 10 percentage point increase in baseline PDV and temporal change in PDV was associated with higher individual-level risk of recent HIV infection at follow-up: adjusted risk ratio 1·85 (95% CI 1·44-2·37) for baseline PDV and 1·81 (1·43-2·29) for change in PDV.

Interpretation: PDV was temporally associated with community-level and individual-level HIV incidence. These data support scale-up of treatment as prevention programmes to reduce HIV incidence and the programmatic use of PDV to monitor community HIV risk potential.

Funding: US National Institutes of Health, Elton John AIDS Foundation.

Figure 1.. Temporal changes in annualized HIV incidence estimates stratified by age group and gender.

Error bars indicate 95% confidence intervals.

Figure 2.. Temporal changes in annualized HIV incidence estimates stratified by community site.

Error bars indicate 95% confidence intervals.

Figure 3.. Community-level correlation between the prevalence of detectable HIV viremia and annualized HIV incidence.

95% confidence intervals for spearman correlation coefficients were estimated from 10,000 bootstrap replications. Community site-level linear regression was used to assess the association between the prevalence of detectable HIV viremia and annualized HIV incidence (β refers to percentage point change in annualized HIV incidence per percentage point increase in prevalence of detectable HIV viremia); the model predicted line of fit is shown in black (panels A, B, C). Models examining HIV incidence in 2016–2017 included adjustment for community intervention status from the primary trial (panels B and C).

Figure 4.. Community-level association of the temporal change in prevalence of detectable HIV viremia with annualized HIV incidence and temporal change in annualized HIV incidence.

Panel A shows the correlation between observed difference in PDV between surveys and annualized HIV incidence in 2016–2017. Panel B shows the adjusted fitted line for the predicted annualized HIV incidence in 2016–2017 as a function the difference in PDV between surveys. Panel C shows the correlation between observed difference in PDV between surveys and observed difference in annualized HIV incidence between surveys. Panel D shows the adjusted fitted line for the predicted change in annualized HIV incidence between surveys as a function of the change in PDV between surveys. Both linear regression models (Panels B, D) included adjustment for community intervention status and the baseline prevalence of detectable HIV viremia in 2012–2013. The prediction bands reflect pointwise 95% confidence intervals.