Estimating the epidemic consequences of HIV prevention gaps among key populations

INTRODUCTION: HIV epidemic appraisals are used to characterize heterogeneity and inequities in the context of the HIV pandemic and the response. However, classic measures used in appraisals have been shown to underestimate disproportionate risks of onward transmission, particularly among key populations. In response, a growing number of modelling studies have quantified the consequences of unmet prevention and treatment needs (prevention gaps) among key populations as a transmission population attributable fraction over time (tPAF(t)). To aid its interpretation and use by programme implementers and policy makers, we outline and discuss a conceptual framework for understanding and estimating the tPAF(t) via transmission modelling as a measure of onward transmission risk from HIV prevention gaps; and discuss properties of the tPAF(t). DISCUSSION: The distribution of onward transmission risks may be defined by who is at disproportionate risk of onward transmission, and under which conditions. The latter reflects prevention gaps, including secondary prevention via treatment: the epidemic consequences of which may be quantified by the tPAF(t). Steps to estimating the tPAF(t) include parameterizing the acquisition and onward transmission risks experienced by the subgroup of interest, defining the most relevant counterfactual scenario, and articulating the time‐horizon of analyses and population among whom to estimate the relative difference in cumulative transmissions; such steps could reflect programme‐relevant questions about onward transmission risks. Key properties of the tPAF(t) include larger onward transmission risks over longer time‐horizons; seemingly mutually exclusive tPAF(t) measures summing to greater than 100%; an opportunity to quantify the magnitude of disproportionate onward transmission risks with a per‐capita tPAF(t); and that estimates are conditional on what has been achieved so far in reducing prevention gaps and maintaining those conditions moving forward as the status quo. CONCLUSIONS: The next generation of HIV epidemic appraisals has the potential to support a more specific HIV response by characterizing heterogeneity in disproportionate risks of onward transmission which are defined and conditioned on the past, current and future prevention gaps across subsets of the population.