Review Article

Mapping the pandemic: a review of Geographical Information Systems‑based spatial modeling of Covid‑19

Mustafa S. Aboalyem, Mohd T. Ismail
Journal of Public Health in Africa | Vol 14, No 11 | a39 | DOI: | © 2024 Mustafa S. Aboalyem, Mohd T. Ismail | This work is licensed under CC Attribution 4.0
Submitted: 14 March 2024 | Published: 30 November 2023

About the author(s)

Mustafa S. Aboalyem, School of Mathematical Sciences, Universiti Sains Malaysia, Gelugor, Pulau Pinang, Malaysia; and, Department of Statistics, Faculty Sciences, Misurata University, Libia
Mohd T. Ismail, School of Mathematical Sciences, Universiti Sains Malaysia, Gelugor, Pulau Pinang, Malaysia

Full Text:



According to the World Health Organization (WHO), COVID‑19 has caused more than 6.5 million deaths, while over 600 million people are infected. With regard to the tools and techniques of disease analysis, spatial analysis is increasingly being used to analyze the impact of COVID‑19. The present review offers an assessment of research that used regional data systems to study the COVID‑19 epidemic published between 2020 and 2022. The research focuses on: categories of the area, authors, methods, and procedures used by the authors and the results of their findings. This input will enable the contrast of different spatial models used for regional data systems with COVID‑19. Our outcomes showed increased use of geographically weighted regression and Moran I spatial statistical tools applied to better spatial and time‑based gauges. We have also found an increase in the use of local models compared to other spatial statistics models/methods.


spatial modeling; COVID‑19; GIS modeling; Moran I statistic; global models


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