Geographic Information Systems in Health Sciences: Spatial Epidemiology, Healthcare Accessibility, Environmental Exposure, and Digital Health

Geographic Information Systems (GIS) provide a spatial framework for integrating health outcomes, population characteristics, healthcare infrastructure, environmental exposures, and transport networks. This review critically synthesizes the research summaries supplied by the author, covering disease mapping and surveillance, spatial epidemiology, environmental-health risk assessment, healthcare accessibility, health-service planning, Web GIS, mobile health, health-information infrastructure, and emerging GeoAI applications. The reviewed literature describes a progression from descriptive disease maps and proximity analysis toward spatial statistics, floating-catchment accessibility methods, location-allocation, space–time surveillance, mobile data integration, and machine-learning-supported analysis. A systematic review of Indian health research by Chandran and Roy (2024), as summarized in the source material, included 58 studies: 30 on disease surveillance and mapping, 14 on health-risk assessment, and 14 on healthcare accessibility. The same review identified inverse-distance weighting, Getis–Ord Gi* hotspot analysis, Moran’s I, and overlay analysis among commonly reported techniques. Across the supplied studies, GIS is consistently positioned as a decision-support technology rather than merely a cartographic tool. However, recurring limitations include incomplete and inconsistent data, weak linkage between potential accessibility and actual service use, ecological fallacy, spatial-scale sensitivity, uneven institutional capacity, limited external validation, interoperability barriers, and privacy risks arising from location-linked health records. A validation- and privacy-centred workflow is proposed to connect data harmonization, spatial analysis, uncertainty assessment, ethical governance, and operational decision-making. Since the supplied notes contain a mixture of systematic reviews, narrative reviews, conceptual papers, and some incomplete bibliographic records, this manuscript is presented as a critical narrative synthesis rather than a new systematic review. Original articles and reference metadata should be verified before journal submission.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-26
DOI
https://doi.org/10.5281/zenodo.23657748
Primary Topic
Data-Driven Disease Surveillance
Type
article
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article

Geographic Information Systems in Health Sciences: Spatial Epidemiology, Healthcare Accessibility, Environmental Exposure, and Digital Health

S. S. Ligade, S. B. Gaikwad, P. A. Pisal
Zenodo (CERN European Organization for Nuclear Research)
Data-Driven Disease Surveillance
article

Geographic Information Systems in Health Sciences: Spatial Epidemiology, Healthcare Accessibility, Environmental Exposure, and Digital Health

S. S. Ligade, S. B. Gaikwad, P. A. Pisal
article en

Abstract

Geographic Information Systems (GIS) provide a spatial framework for integrating health outcomes, population characteristics, healthcare infrastructure, environmental exposures, and transport networks. This review critically synthesizes the research summaries supplied by the author, covering disease mapping and surveillance, spatial epidemiology, environmental-health risk assessment, healthcare accessibility, health-service planning, Web GIS, mobile health, health-information infrastructure, and emerging GeoAI applications. The reviewed literature describes a progression from descriptive disease maps and proximity analysis toward spatial statistics, floating-catchment accessibility methods, location-allocation, space–time surveillance, mobile data integration, and machine-learning-supported analysis. A systematic review of Indian health research by Chandran and Roy (2024), as summarized in the source material, included 58 studies: 30 on disease surveillance and mapping, 14 on health-risk assessment, and 14 on healthcare accessibility. The same review identified inverse-distance weighting, Getis–Ord Gi* hotspot analysis, Moran’s I, and overlay analysis among commonly reported techniques. Across the supplied studies, GIS is consistently positioned as a decision-support technology rather than merely a cartographic tool. However, recurring limitations include incomplete and inconsistent data, weak linkage between potential accessibility and actual service use, ecological fallacy, spatial-scale sensitivity, uneven institutional capacity, limited external validation, interoperability barriers, and privacy risks arising from location-linked health records. A validation- and privacy-centred workflow is proposed to connect data harmonization, spatial analysis, uncertainty assessment, ethical governance, and operational decision-making. Since the supplied notes contain a mixture of systematic reviews, narrative reviews, conceptual papers, and some incomplete bibliographic records, this manuscript is presented as a critical narrative synthesis rather than a new systematic review. Original articles and reference metadata should be verified before journal submission.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 12%
Data-Driven Disease Surveillance
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Geographic Information Systems in Health Sciences: Spatial Epidemiology, Healthcare Accessibility, Environmental Exposure, and Digital Health — S. S. Ligade, S. B. Gaikwad, et al. · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS