A Bayesian approach to estimate changes in condom use from limited human immunodeficiency virus prevalence data.

J Dureau,K Kalogeropoulos,P Vickerman,M.-C Boily,M Pickles

doi:10.1111/rssc.12116

Abstract

SummaryEvaluation of large‐scale intervention programmes against human immunodeficiency virus (HIV) is becoming increasingly important, but impact estimates frequently hinge on knowledge of changes in behaviour such as the frequency of condom use over time, or other self‐reported behaviour changes, for which we generally have limited or potentially biased data. We employ a Bayesian inference methodology that incorporates an HIV transmission dynamics model to estimate condom use time trends from HIV prevalence data. Estimation is implemented via particle Markov chain Monte Carlo methods, applied for the first time in this context. The preliminary choice of the formulation for the time varying parameter reflecting the proportion of condom use is critical in the context studied, because of the very limited amount of condom use and HIV data available. We consider various novel formulations to explore the trajectory of condom use over time, based on diffusion‐driven trajectories and smooth sigmoid curves. Numerical simulations indicate that informative results can be obtained regarding the amplitude of the increase in condom use during an intervention, with good levels of sensitivity and specificity performance in effectively detecting changes. The application of this method to a real life problem demonstrates how it can help in evaluating HIV interventions based on a small number of prevalence estimates, and it opens the way to similar applications in different contexts.

Highlights

Significant resources are being committed to implement large-scale interventions against infectious diseases such as the human immunodeficiency virus (HIV), that killed an estimated 2 million individuals in 2008 (UNAIDS and World Health Organization, 2009)
We develop a Bayesian approach to evaluate the Avahan programme, which is a large-scale HIV and acquired immune deficiency syndrome intervention targeted to high-risk groups, through the estimation of the evolution of condom use from the available HIV prevalence data
The work that we present in this paper operates in a similar context to that in Pickles et al (2010) but, rather than making explicit assumptions about the evolution of condom use based on additional sources, we aim to develop a Bayesian inference framework exploring the entire space of the condom use trajectories without any reference to the 2003 Avahan intervention, female sex workers (FSWs) surveys or condom distribution data

Summary

Introduction

Significant resources are being committed to implement large-scale interventions against infectious diseases such as the human immunodeficiency virus (HIV), that killed an estimated 2 million individuals in 2008 (UNAIDS and World Health Organization, 2009). Increasing attention is given to the evaluation of these large-scale intervention programmes to understand what still needs to be done to control the epidemic and eventually to achieve elimination. Even if antiretroviral therapy has become an important component of large-scale prevention interventions, the use of condoms and circumcision remain important strategies for reducing.

Objectives

Methods

Results

Discussion

Conclusion