Geospatial Epidemiology in Low-Resource Settings: Advances, Challenges, and Future Directions

Geospatial epidemiology has emerged as a critical tool to strengthen disease surveillance, resource allocation, and health equity in low-resource settings. This narrative review synthesizes evidence on the recent applications, methodological advances, and implementation challenges of geospatial approaches across infectious diseases, maternal and child health, noncommunicable diseases, climate-sensitive conditions, and humanitarian contexts. Key sources, including GIS, remote sensing, population grids, Demographic and Health Surveys, and routine health information systems, have enabled increasingly refined spatial analyses, from malaria and cholera hotspot detection to accessibility modeling for maternal care and climate-health early warning systems. However, persistent limitations remain, including incomplete surveillance data, inaccurate or displaced geocoding, unstable population denominators, and constrained technical and institutional capacity, which restrict the consistent translation of spatial insights into policy actions. Ethical concerns related to data privacy and governance further complicate the use of high-resolution mapping for vulnerable populations. We identify emerging opportunities to address these gaps, including the integration of artificial intelligence, strengthening of national spatial data infrastructure, community-based geospatial data collection, and linkage with civil registration and identification systems under robust governance frameworks. Institutionalizing geospatial capacity within health systems is essential for transforming spatial analytics from episodic research exercises to a sustainable foundation for precision public health and equitable service delivery in low-resource settings.