Estimating Population Viral Load Contextual Exposure Using GPS-Derived Activity Spaces in Rural South Africa

TL;DR

This paper develops new GPS-based methods to estimate HIV exposure risk in rural South Africa by analyzing individual mobility patterns and local viral load data.

Contribution

It introduces an analytical framework combining GPS-derived activity spaces with HIV viral load estimates to assess exposure risk.

Findings

Mobility patterns vary systematically by sex and age.

Extended activity spaces correlate with higher HIV exposure risk.

Methodology enables identification of individuals at elevated HIV acquisition risk.

Abstract

This article introduces novel methodologies for estimating contextual exposure to HIV population viral load using GPS data. We propose a comprehensive analytical framework comprising (i) local (grid-cell level) estimation of HIV population viral load, (ii) derivation of individual activity spaces from GPS trajectories, and (iii) quantification of contextual exposure to HIV within these activity spaces. We integrate HIV surveillance and sociodemographic survey data with GPS-based mobility data collected in rural KwaZulu-Natal, South Africa, to characterize mobility patterns among young adults aged 20-30 years. Using derived measures of mobility and contextual exposure, we assess whether participants' sex and age systematically influence the magnitude, configuration, and heterogeneity of their mobility patterns. Furthermore, we describe analytical approaches to examine how contextual exposure to HIV evolves as activity spaces extend beyond static residential locations, outlining procedures to identify GPS-tracked participants at elevated risk of HIV acquisition. KEYWORDS: Population viral load exposure; GPS-based mobility analysis; Activity space