Evolving HIV epidemics: the urgent need to refocus on populations with risk

Abstract

Purpose of review: To explore the comparative importance of HIV infections among key populations and their intimate partners as HIV epidemics evolve, and to review implications for guiding responses.

Recent findings: Even as concentrated epidemics evolve, new infections among current and former key population members and their intimate partners dominate new infections. Prevalent infections in the general population grow primarily because of key population turnover and infections among their intimate partners. In generalized epidemic settings, data and analysis on key populations are often inadequate to assess the impact of key population-focused responses, so they remain limited in coverage and under resourced. Models must incorporate downstream infections in comparing impacts of alternative responses.

Summary: Recognize that every epidemic is unique, moving beyond the overly simplistic concentrated/generalized epidemic paradigm that can misdirect resources. Guide HIV responses by gathering and using locally relevant data, understanding risk heterogeneity, and applying modeling at both national and sub-national levels to optimize resource allocations among different populations for greatest impact. Translate this improved understanding into clear, unequivocal advice for policymakers on where to focus for impact, breaking them free of the generalized/concentrated paradigm limiting their thinking and affecting their decisions.

Box 1

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FIGURE 1

(a) The number of prevalent, that is, current, HIV infections in 11 Asian countries in 2017 by subpopulation, and (b) the number of new HIV infections by subpopulation. The countries have been ordered from left to right based on the proportion of current infections among key populations. The figures are derived from national models developed by local AEM teams as submitted to UNAIDS in 2018. Values are for female sex workers (FSW), clients, MSM, transgenders (TG), people who inject drugs (PWID) and the rest of the male and female population. AEM, AIDS Epidemic Model.

FIGURE 2

The evolution of (a) current infections and (b) new infections by subpopulation from 1990 to 2020 aggregated across the 11 AIDS Epidemic Model countries. The gray bars show the evolution of current and new infections in the general population (rest of males/rest of females).

FIGURE 3

(a) The number of HIV+ individuals leaving each key population to return to the ‘general population’ in Thailand from the start of the epidemic to 2017, and (b) infections among nonkey population women in the 11 countries over time by route of infection.

FIGURE 4

Downstream infections averted in the Indonesia model if 1000 female sex worker infections are prevented in 2018. By 2030, this will avert 9200 infections among clients, 640 additional infections among sex workers, 420 infections among males not in key populations and 4200 infections among females not in key populations.

FIGURE 5

Distribution of new infections by sub-population in different regions of the world in 2017 as estimated by UNAIDS. Source: Miles to Go 2018 [21].

FIGURE 6

HIV prevalence among (a) Female sex worker and (b) MSM compared against national prevalence among those aged 15–49 years for Eastern and Southern Africa (ESA in orange) and Western and Central Africa (WCA in blue). Although not nationally representative in most cases, they give an idea of the range of values being observed in the regions. Source: UNAIDS Data 2018 [47].

FIGURE 7

Size estimates for (a) Sex worker and (b) MSM as a proportion of 15–49-year-old population of the same sex for Eastern and Southern Africa (ESA in orange) and Western and Central Africa (WCA in blue). Source: UNAIDS Data 2018 [47].