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Discovering spatiotemporal patterns of COVID-19 pandemic in South Korea

A novel severe acute respiratory syndrome coronavirus 2 emerged in December 2019, and it took only a few months for WHO to declare COVID-19 as a pandemic in March 2020. It is very challenging to discover complex spatial–temporal transmission mechanisms. However, it is crucial to capture essential fe...

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Autores principales: Kim, Sungchan, Kim, Minseok, Lee, Sunmi, Lee, Young Ju
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8714822/
https://www.ncbi.nlm.nih.gov/pubmed/34963690
http://dx.doi.org/10.1038/s41598-021-03487-2
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author Kim, Sungchan
Kim, Minseok
Lee, Sunmi
Lee, Young Ju
author_facet Kim, Sungchan
Kim, Minseok
Lee, Sunmi
Lee, Young Ju
author_sort Kim, Sungchan
collection PubMed
description A novel severe acute respiratory syndrome coronavirus 2 emerged in December 2019, and it took only a few months for WHO to declare COVID-19 as a pandemic in March 2020. It is very challenging to discover complex spatial–temporal transmission mechanisms. However, it is crucial to capture essential features of regional-temporal patterns of COVID-19 to implement prompt and effective prevention or mitigation interventions. In this work, we develop a novel framework of compatible window-wise dynamic mode decomposition (CwDMD) for nonlinear infectious disease dynamics. The compatible window is a selected representative subdomain of time series data, in which compatibility between spatial and temporal resolutions is established so that DMD can provide meaningful data analysis. A total of four compatible windows have been selected from COVID-19 time-series data from January 20, 2020, to May 10, 2021, in South Korea. The spatiotemporal patterns of these four windows are then analyzed. Several hot and cold spots were identified, their spatial–temporal relationships, and some hidden regional patterns were discovered. Our analysis reveals that the first wave was contained in the Daegu and Gyeongbuk areas, but it spread rapidly to the whole of South Korea after the second wave. Later on, the spatial distribution is seen to become more homogeneous after the third wave. Our analysis also identifies that some patterns are not related to regional relevance. These findings have then been analyzed and associated with the inter-regional and local characteristics of South Korea. Thus, the present study is expected to provide public health officials helpful insights for future regional-temporal specific mitigation plans.
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spelling pubmed-87148222022-01-05 Discovering spatiotemporal patterns of COVID-19 pandemic in South Korea Kim, Sungchan Kim, Minseok Lee, Sunmi Lee, Young Ju Sci Rep Article A novel severe acute respiratory syndrome coronavirus 2 emerged in December 2019, and it took only a few months for WHO to declare COVID-19 as a pandemic in March 2020. It is very challenging to discover complex spatial–temporal transmission mechanisms. However, it is crucial to capture essential features of regional-temporal patterns of COVID-19 to implement prompt and effective prevention or mitigation interventions. In this work, we develop a novel framework of compatible window-wise dynamic mode decomposition (CwDMD) for nonlinear infectious disease dynamics. The compatible window is a selected representative subdomain of time series data, in which compatibility between spatial and temporal resolutions is established so that DMD can provide meaningful data analysis. A total of four compatible windows have been selected from COVID-19 time-series data from January 20, 2020, to May 10, 2021, in South Korea. The spatiotemporal patterns of these four windows are then analyzed. Several hot and cold spots were identified, their spatial–temporal relationships, and some hidden regional patterns were discovered. Our analysis reveals that the first wave was contained in the Daegu and Gyeongbuk areas, but it spread rapidly to the whole of South Korea after the second wave. Later on, the spatial distribution is seen to become more homogeneous after the third wave. Our analysis also identifies that some patterns are not related to regional relevance. These findings have then been analyzed and associated with the inter-regional and local characteristics of South Korea. Thus, the present study is expected to provide public health officials helpful insights for future regional-temporal specific mitigation plans. Nature Publishing Group UK 2021-12-28 /pmc/articles/PMC8714822/ /pubmed/34963690 http://dx.doi.org/10.1038/s41598-021-03487-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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
Kim, Sungchan
Kim, Minseok
Lee, Sunmi
Lee, Young Ju
Discovering spatiotemporal patterns of COVID-19 pandemic in South Korea
title Discovering spatiotemporal patterns of COVID-19 pandemic in South Korea
title_full Discovering spatiotemporal patterns of COVID-19 pandemic in South Korea
title_fullStr Discovering spatiotemporal patterns of COVID-19 pandemic in South Korea
title_full_unstemmed Discovering spatiotemporal patterns of COVID-19 pandemic in South Korea
title_short Discovering spatiotemporal patterns of COVID-19 pandemic in South Korea
title_sort discovering spatiotemporal patterns of covid-19 pandemic in south korea
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8714822/
https://www.ncbi.nlm.nih.gov/pubmed/34963690
http://dx.doi.org/10.1038/s41598-021-03487-2
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