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

2026-04-29

AI Summary

This study challenges the conventional residence-centered paradigm of HIV exposure assessment by precisely characterizing individuals’ dynamic risk of encountering community viral load within their daily activity spaces. Integrating longitudinal HIV surveillance, sociodemographic surveys, and GPS trajectory data from rural South African youth, the research constructs a gridded community viral load model, delineates individual activity spaces, and quantifies intra-activity-space exposure levels. Methodologically, it bridges epidemiology and geographic information science, pioneering the integration of GPS-derived activity spaces with community viral load to enable personalized, dynamic environmental risk assessment. The findings reveal systematic influences of gender and age on both activity space characteristics and HIV exposure, and propose an operational framework for identifying high-risk individuals.

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

Problem

• Population viral load exposure
• GPS-based mobility analysis
• Activity space
• HIV contextual exposure
• Mobility patterns

Innovation

• Population viral load exposure
• GPS-based mobility analysis
• Activity space
• Contextual exposure
• HIV risk assessment