https://doi.org/10.4081/gh.2024.1264

A conceptional model integrating geographic information systems (GIS) and social media data for disease exposure assessment

Vol. 19 No. 1 (2024)
Submitted: 27 December 2023
Accepted: 28 February 2024
Published: 28 March 2024
Disease map, environmental exposure, GIS, individual mobility patterns, social media
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Authors

Jerry Enoe
Department of Geomatics Engineering and Land Management, The University of the West Indies, St. Augustine, Trinidad and Tobago.
Michael Sutherland
https://orcid.org/0000-0001-7158-569X
Department of Geomatics Engineering and Land Management, The University of the West Indies, St. Augustine, Trinidad and Tobago.
Dexter Davis
Department of Geomatics Engineering and Land Management, The University of the West Indies, St. Augustine, Trinidad and Tobago.
Bheshem Ramlal
https://orcid.org/0000-0002-3000-6214
Department of Geomatics Engineering and Land Management, The University of the West Indies, St. Augustine, Trinidad and Tobago.
Charisse Griffith-Charles
Department of Geomatics Engineering and Land Management, The University of the West Indies, St. Augustine, Trinidad and Tobago.
Keston H. Bhola
Department of Computers and Technology, School of Arts and Science, St George's University, Grenada.
Elsai Mati Asefa
Elsai.mati@haramaya.edu.et
School of Environmental Health, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia.

Although previous studies have acknowledged the potential of geographic information systems (GIS) and social media data (SMD) in assessment of exposure to various environmental risks, none has presented a simple, effective and user-friendly tool. This study introduces a conceptual model that integrates individual mobility patterns extracted from social media, with the geographic footprints of infectious diseases and other environmental agents utilizing GIS. The efficacy of the model was independently evaluated for selected case studies involving lead in the ground; particulate matter in the air; and an infectious, viral disease (COVID- 19). A graphical user interface (GUI) was developed as the final output of this study. Overall, the evaluation of the model demonstrated feasibility in successfully extracting individual mobility patterns, identifying potential exposure sites and quantifying the frequency and magnitude of exposure. Importantly, the novelty of the developed model lies not merely in its efficiency in integrating GIS and SMD for exposure assessment, but also in considering the practical requirements of health practitioners. Although the conceptual model, developed together with its associated GUI, presents a promising and practical approach to assessment of the exposure to environmental risks discussed here, its applicability, versatility and efficacy extends beyond the case studies presented in this study.

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How to Cite

Enoe , J., Sutherland, M., Davis, D., Ramlal, B., Griffith-Charles , C., Bhola, K. H., & Asefa, E. M. (2024). A conceptional model integrating geographic information systems (GIS) and social media data for disease exposure assessment. Geospatial Health, 19(1). https://doi.org/10.4081/gh.2024.1264
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