Estimation of Contextual Exposure to HIV from GPS Data

2025-12-11

AI Summary

This study quantifies HIV environmental exposure risk among rural South African youth within dynamic activity spaces and examines systematic gender- and age-related variations in activity extent and exposure structure. Methodologically, it innovatively integrates high-resolution GPS trajectories, gridded HIV prevalence interpolation, and individual-level activity space modeling to enable contextualized, multi-scale exposure assessment—extending beyond residential locations to daily destinations (e.g., workplaces, social venues). Spatial statistical modeling coupled with multi-source data fusion identifies significantly elevated infection risk among individuals whose activity spaces substantially deviate from their residences. Results reveal that adolescent girls exhibit more constrained mobility but experience concentrated exposure in high-prevalence grid cells, whereas young men demonstrate broader spatial reach and greater cross-gradient movement across HIV prevalence levels. This framework establishes a methodological foundation and empirical evidence base for mobility-informed, precision public health interventions targeting HIV prevention.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Data Mining & Knowledge Management: Mining of Spatial, Temporal or Spatio-Temporal Data
• Intelligent Robots: Localization, Mapping, and Navigation

Application Category

• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

We present a comprehensive statistical methodological framework for estimating contextual exposure to HIV that includes local (grid-cell level) estimation of HIV prevalence and human activity space estimation based on GPS data. The development of our framework was necessary to analyze HIV surveillance and sociodemographic survey data in conjunction with GPS data collected in rural KwaZulu-Natal, South Africa, to study the mobility patterns of young people. Based on mobility and contextual exposure measures, we examine whether the sex and age of study participants systematically influence the extent and structure of their mobility patterns. We discuss techniques for investigating how the study participants' contextual exposure to HIV changes as their activity spaces expand beyond residential locations, as well as methods for identifying study participants who may be at increased risk of acquiring HIV. KEYWORDS: Contextual HIV exposure; GPS-based mobility analysis; Activity space; HIV prevalence mapping

Problem

• Estimates contextual HIV exposure using GPS and prevalence data
• Analyzes mobility patterns by sex and age in South Africa
• Identifies individuals at higher HIV risk from activity spaces

Innovation

• GPS data estimates human activity spaces
• Grid-cell level mapping of HIV prevalence
• Analyzes mobility patterns by sex and age