Inference for Within- and Between-Partnership Transmission Rates for HIV Infection

TL;DR

This paper develops a stochastic SI pair model to estimate HIV transmission rates within and between serodiscordant couples, accounting for gender differences, to inform prevention strategies and generalize to other epidemiological contexts.

Contribution

The study introduces a likelihood-based inference method for a stochastic SI pair model that estimates HIV transmission parameters within and between couples, including gender-specific differences.

Findings

Estimated transmission rates within couples.

Quantified external infection introduction rates.

Model accounts for gender differences in transmission dynamics.

Abstract

HIV transmission within serodiscordant couples remains a significant public health challenge, particularly in sub-Saharan Africa. Estimating the rate of such infection, alongside the rates of introduction of infection from outside the partnership, is a special case of the more general epidemiological challenge of inferring intensities of within- and between-group intensities of transmission. This study presents a stochastic susceptible-infected (SI) pair model for estimating key epidemiological parameters governing HIV transmission within and between couples, which we further extend to account for gender-specific differences in infection dynamics. Using a likelihood-based inference approach, we estimate transmission parameters and associated uncertainty from observed data. These values can be used to inform infection prevention strategies for HIV, and the methodology proposed can be generalised to other epidemiological settings.