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An analysis of the dynamic spatial spread of COVID-19 across South Korea

The first case of coronavirus disease 2019 (COVID-19) in South Korea was confirmed on January 20, 2020, approximately three weeks after the report of the first COVID-19 case in Wuhan, China. By September 15, 2021, the number of cases in South Korea had increased to 277,989. Thus, it is important to...

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Autores principales: Kang, Dayun, Choi, Jungsoon, Kim, Yeonju, Kwon, Donghyok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9171729/
https://www.ncbi.nlm.nih.gov/pubmed/35672439
http://dx.doi.org/10.1038/s41598-022-13301-2
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author Kang, Dayun
Choi, Jungsoon
Kim, Yeonju
Kwon, Donghyok
author_facet Kang, Dayun
Choi, Jungsoon
Kim, Yeonju
Kwon, Donghyok
author_sort Kang, Dayun
collection PubMed
description The first case of coronavirus disease 2019 (COVID-19) in South Korea was confirmed on January 20, 2020, approximately three weeks after the report of the first COVID-19 case in Wuhan, China. By September 15, 2021, the number of cases in South Korea had increased to 277,989. Thus, it is important to better understand geographical transmission and design effective local-level pandemic plans across the country over the long term. We conducted a spatiotemporal analysis of weekly COVID-19 cases in South Korea from February 1, 2020, to May 30, 2021, in each administrative region. For the spatial domain, we first covered the entire country and then focused on metropolitan areas, including Seoul, Gyeonggi-do, and Incheon. Moran’s I and spatial scan statistics were used for spatial analysis. The temporal variation and dynamics of COVID-19 cases were investigated with various statistical visualization methods. We found time-varying clusters of COVID-19 in South Korea using a range of statistical methods. In the early stage, the spatial hotspots were focused in Daegu and Gyeongsangbuk-do. Then, metropolitan areas were detected as hotspots in December 2020. In our study, we conducted a time-varying spatial analysis of COVID-19 across the entirety of South Korea over a long-term period and found a powerful approach to demonstrating the current dynamics of spatial clustering and understanding the dynamic effects of policies on COVID-19 across South Korea. Additionally, the proposed spatiotemporal methods are very useful for understanding the spatial dynamics of COVID-19 in South Korea.
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spelling pubmed-91717292022-06-08 An analysis of the dynamic spatial spread of COVID-19 across South Korea Kang, Dayun Choi, Jungsoon Kim, Yeonju Kwon, Donghyok Sci Rep Article The first case of coronavirus disease 2019 (COVID-19) in South Korea was confirmed on January 20, 2020, approximately three weeks after the report of the first COVID-19 case in Wuhan, China. By September 15, 2021, the number of cases in South Korea had increased to 277,989. Thus, it is important to better understand geographical transmission and design effective local-level pandemic plans across the country over the long term. We conducted a spatiotemporal analysis of weekly COVID-19 cases in South Korea from February 1, 2020, to May 30, 2021, in each administrative region. For the spatial domain, we first covered the entire country and then focused on metropolitan areas, including Seoul, Gyeonggi-do, and Incheon. Moran’s I and spatial scan statistics were used for spatial analysis. The temporal variation and dynamics of COVID-19 cases were investigated with various statistical visualization methods. We found time-varying clusters of COVID-19 in South Korea using a range of statistical methods. In the early stage, the spatial hotspots were focused in Daegu and Gyeongsangbuk-do. Then, metropolitan areas were detected as hotspots in December 2020. In our study, we conducted a time-varying spatial analysis of COVID-19 across the entirety of South Korea over a long-term period and found a powerful approach to demonstrating the current dynamics of spatial clustering and understanding the dynamic effects of policies on COVID-19 across South Korea. Additionally, the proposed spatiotemporal methods are very useful for understanding the spatial dynamics of COVID-19 in South Korea. Nature Publishing Group UK 2022-06-07 /pmc/articles/PMC9171729/ /pubmed/35672439 http://dx.doi.org/10.1038/s41598-022-13301-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Kang, Dayun
Choi, Jungsoon
Kim, Yeonju
Kwon, Donghyok
An analysis of the dynamic spatial spread of COVID-19 across South Korea
title An analysis of the dynamic spatial spread of COVID-19 across South Korea
title_full An analysis of the dynamic spatial spread of COVID-19 across South Korea
title_fullStr An analysis of the dynamic spatial spread of COVID-19 across South Korea
title_full_unstemmed An analysis of the dynamic spatial spread of COVID-19 across South Korea
title_short An analysis of the dynamic spatial spread of COVID-19 across South Korea
title_sort analysis of the dynamic spatial spread of covid-19 across south korea
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9171729/
https://www.ncbi.nlm.nih.gov/pubmed/35672439
http://dx.doi.org/10.1038/s41598-022-13301-2
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