Spatial statistical methodologies in COVID-19 Studies: A systematic review
1 Faculty of Nursing, East Asia University of Technology, Hanoi, Vietnam.
2 Preclinical Research Center, Nam Dinh University of Nursing, Nam Dinh, Vietnam.
Review
World Journal of Biology Pharmacy and Health Sciences, 2023, 15(03), 068–075.
Article DOI: 10.30574/wjbphs.2023.15.3.0389
Publication history:
Received on 08 August 2023; revised on 16 September 2023; accepted on 19 September 2023
Abstract:
Objective: As of August 2023, COVID-19 had claimed 7 million lives, making it the pandemic with the highest mortality rate. Therefore, The use of cutting-edge technologies and methods is essential when battling the COVID-19 epidemic. This paper aims to systematically review and synthetize applications of spatial statistical methodologies in the analysis of COVID-19.
Material and Methods: 55 articles in total were screened from four main digital databases including Web of Science, SCOPUS, PubMed/MEDLINE, and Google schoolar. Three distinct concerns with the use of spatial statistical techniques in the analysis of COVID-19 are discussed, namely (i) applications of spatial regressions in the evaluation of COVID-19's effects, (ii) COVID-19 mapping using of hotspots and spatial clustering analyses, and (iii) applications of interpolation and geostatistics on COVID-19 studies, respectively.
Results: Spatial regressions can support the assessment of the COVID-19 impacts on social-economy and environment. Whereas, hotspots and spatial clustering analysis can help effectively on COVID-19 mapping. Last but not least, geostatistics and interpolation are crucial for predicting COVID-19.
Conclusion: This review not only emphasises the significance of spatial statistical techniques in COVID-19 studies, but it also sheds light on the practical applications of spatial statistics in COVID-19 research.
Keywords:
Spatial statistics ; Spatial regressions ; Hotspot ; Spatial clustering ; Applications ; COVID-19 ; Review
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0