Affiliation:
1. Universiti Sains Malaysia
Abstract
Abstract
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.
Publisher
Research Square Platform LLC
Reference70 articles.
1. Alcântara E, Mantovani J, Rotta L, Park E, Rodrigues T, Carvalho F, C, Souza Filho C (2020) R. Investigating spatiotemporal patterns of the COVID-19 in São Paulo State, Brazil. MedRxiv, 2020
2. GIS application for modeling covid-19 risk in the Makkah region, Saudi Arabia, based on population and population density;Alkhaldy I;Egypt J Environ Change,2020
3. Spatial distribution and determinants of acute respiratory infection among under-five children in Ethiopia: Ethiopian Demographic Health Survey 2016;Amsalu E;PLoS ONE,2019
4. Spatial analysis of risk of morbidity and mortality by COVID-19 in Europe and the Mediterranean in the year 2020;Andrades-Grassi J;Cuad Geograficos,2021
5. Local indicators of spatial association-LISA;Anselin L;Geographical Anal,1995