Concurrent partnerships, acute infection and HIV epidemic dynamics among young adults in Zimbabwe

Abstract

This paper explores the roles of acute infection and concurrent partnerships in HIV transmission dynamics among young adults in Zimbabwe using realistic representations of the partnership network and all published estimates of stage-specific infectivity. We use dynamic exponential random graph models to estimate partnership network parameters from an empirical study of sexual behavior and drive a stochastic simulation of HIV transmission through this dynamic network. Our simulated networks match observed frequencies and durations of short- and long-term partnerships, with concurrency patterns specific to gender and partnership type. Our findings suggest that, at current behavior levels, the epidemic cannot be sustained in this population without both concurrency and acute infection; removing either brings transmission below the threshold for persistence. With both present, we estimate 20-25% of transmissions stem from acute-stage infections, 30-50% from chronic-stage, and 30-45% from AIDS-stage. The impact of acute infection is strongly moderated by concurrency. Reducing this impact by reducing concurrency could potentially end the current HIV epidemic in Zimbabwe.

Fig. 1

This example network is drawn from the distribution of networks specified by the baseline ERGM. It represents a typical cross-sectional slice from the simulated dynamic network, and preserves the empirical summary statistics observed in the Zimbabwe data

Fig. 2

a Proportion of new infections by stage over time, averaged across all ten Hollingsworth base model runs. b Cumulative density function for transmission events by age of transmitter. The y-axis represents the cumulative number of transmission events from source partners who have been infected no more than the number of months on the x-axis, divided by the total number of transmission events. Each line represents one of the ten Hollingsworth base model runs. The horizontal line at the end of the age axis is due to the assumption of no sex during the last 10 months of infection for this model