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- W4386999745 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." @default.
- W4386999745 created "2023-09-25" @default.
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- W4386999745 date "2023-09-30" @default.
- W4386999745 modified "2023-09-28" @default.
- W4386999745 title "Spatial statistical methodologies in COVID-19 Studies: A systematic review" @default.
- W4386999745 doi "https://doi.org/10.30574/wjbphs.2023.15.3.0389" @default.
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