An analysis of the dynamic spatial spread of COVID-19 across South Korea
Abstract 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 impo...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-06-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-13301-2 |
| _version_ | 1828796709061263360 |
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| author | Dayun Kang Jungsoon Choi Yeonju Kim Donghyok Kwon |
| author_facet | Dayun Kang Jungsoon Choi Yeonju Kim Donghyok Kwon |
| author_sort | Dayun Kang |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-12T04:27:37Z |
| format | Article |
| id | doaj.art-038ce9c8d92940b98d0e78e75d148151 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-12T04:27:37Z |
| publishDate | 2022-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-038ce9c8d92940b98d0e78e75d1481512022-12-22T00:38:09ZengNature PortfolioScientific Reports2045-23222022-06-0112111310.1038/s41598-022-13301-2An analysis of the dynamic spatial spread of COVID-19 across South KoreaDayun Kang0Jungsoon Choi1Yeonju Kim2Donghyok Kwon3Department of Applied Statistics, Hanyang UniversityDepartment of Mathematics, Hanyang UniversityDivision of Public Health Emergency Response Research, Korea Disease Control and Prevention AgencyDivision of Public Health Emergency Response Research, Korea Disease Control and Prevention AgencyAbstract 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.https://doi.org/10.1038/s41598-022-13301-2 |
| spellingShingle | Dayun Kang Jungsoon Choi Yeonju Kim Donghyok Kwon An analysis of the dynamic spatial spread of COVID-19 across South Korea Scientific Reports |
| 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 |
| url | https://doi.org/10.1038/s41598-022-13301-2 |
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