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.
%0 Journal Article
%1 thi_quynh_nguyen_2024_10704751
%A Nguyen, Thi-Quynh
%A Mai, Thi-Yen
%D 2024
%J World Journal of Biology Pharmacy and Health Sciences
%K Spatial statistics
%N 3
%P 068–075
%R 10.30574/wjbphs.2023.15.3.0389
%T Spatial statistical methodologies in COVID-19 Studies: A systematic review
%U https://wjbphs.com/content/spatial-statistical-methodologies-covid-19-studies-systematic-review
%V 15
%X 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.
@article{thi_quynh_nguyen_2024_10704751,
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.},
added-at = {2024-03-17T09:50:18.000+0100},
author = {Nguyen, Thi-Quynh and Mai, Thi-Yen},
biburl = {https://www.bibsonomy.org/bibtex/2809b1c0c1d168c8f1c6b805a6361bb5b/wjbphsjournal},
doi = {10.30574/wjbphs.2023.15.3.0389},
interhash = {3187bb7d0b96d62f65403a68c8c46690},
intrahash = {809b1c0c1d168c8f1c6b805a6361bb5b},
issn = {2582-5542},
journal = {{World Journal of Biology Pharmacy and Health Sciences}},
keywords = {Spatial statistics},
month = feb,
number = 3,
pages = {068–075},
timestamp = {2024-03-17T09:50:18.000+0100},
title = {Spatial statistical methodologies in COVID-19 Studies: A systematic review},
url = {https://wjbphs.com/content/spatial-statistical-methodologies-covid-19-studies-systematic-review},
volume = 15,
year = 2024
}