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Exploring spatiotemporal patterns of COVID-19 infection in Nagasaki Prefecture in Japan using prospective space-time scan statistics from April 2020 to April 2022

BACKGROUND: Up to April 2022, there were six waves of infection of coronavirus disease 2019 (COVID-19) in Japan. As the outbreaks continue to grow, it is critical to detect COVID-19’s clusters to allocate health resources and improve decision-making substantially. This study aimed to identify active...

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Autores principales: Lu, Yixiao, Cai, Guoxi, Hu, Zhijian, He, Fei, Jiang, Yixian, Aoyagi, Kiyoshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9315091/
https://www.ncbi.nlm.nih.gov/pubmed/35883103
http://dx.doi.org/10.1186/s13690-022-00921-3
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author Lu, Yixiao
Cai, Guoxi
Hu, Zhijian
He, Fei
Jiang, Yixian
Aoyagi, Kiyoshi
author_facet Lu, Yixiao
Cai, Guoxi
Hu, Zhijian
He, Fei
Jiang, Yixian
Aoyagi, Kiyoshi
author_sort Lu, Yixiao
collection PubMed
description BACKGROUND: Up to April 2022, there were six waves of infection of coronavirus disease 2019 (COVID-19) in Japan. As the outbreaks continue to grow, it is critical to detect COVID-19’s clusters to allocate health resources and improve decision-making substantially. This study aimed to identify active clusters of COVID-19 in Nagasaki Prefecture and form the spatiotemporal pattern of high-risk areas in different infection periods. METHODS: We used the prospective space-time scan statistic to detect emerging COVID-19 clusters and examine the relative risk in five consecutive periods from April 1, 2020 to April 7, 2022, in Nagasaki Prefecture. RESULTS: The densely inhabited districts (DIDs) in Nagasaki City have remained the most affected areas since December 2020. Most of the confirmed cases in the early period of each wave had a history of travelling to other prefectures. Community-level transmissions are suggested by the quick expansion of spatial clusters from urban areas to rural areas and remote islands. Moreover, outbreaks in welfare facilities and schools may lead to an emerging cluster in Nagasaki Prefecture’s rural areas. CONCLUSIONS: This study gives an overall analysis of the transmission dynamics of the COVID-19 pandemic in Nagasaki Prefecture, based on the number of machi-level daily cases. Furthermore, the findings in different waves can serve as references for subsequent pandemic prevention and control. This method helps the health authorities track and investigate outbreaks of COVID-19 that are specific to these environments, especially in rural areas where healthcare resources are scarce. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13690-022-00921-3.
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spelling pubmed-93150912022-07-26 Exploring spatiotemporal patterns of COVID-19 infection in Nagasaki Prefecture in Japan using prospective space-time scan statistics from April 2020 to April 2022 Lu, Yixiao Cai, Guoxi Hu, Zhijian He, Fei Jiang, Yixian Aoyagi, Kiyoshi Arch Public Health Research BACKGROUND: Up to April 2022, there were six waves of infection of coronavirus disease 2019 (COVID-19) in Japan. As the outbreaks continue to grow, it is critical to detect COVID-19’s clusters to allocate health resources and improve decision-making substantially. This study aimed to identify active clusters of COVID-19 in Nagasaki Prefecture and form the spatiotemporal pattern of high-risk areas in different infection periods. METHODS: We used the prospective space-time scan statistic to detect emerging COVID-19 clusters and examine the relative risk in five consecutive periods from April 1, 2020 to April 7, 2022, in Nagasaki Prefecture. RESULTS: The densely inhabited districts (DIDs) in Nagasaki City have remained the most affected areas since December 2020. Most of the confirmed cases in the early period of each wave had a history of travelling to other prefectures. Community-level transmissions are suggested by the quick expansion of spatial clusters from urban areas to rural areas and remote islands. Moreover, outbreaks in welfare facilities and schools may lead to an emerging cluster in Nagasaki Prefecture’s rural areas. CONCLUSIONS: This study gives an overall analysis of the transmission dynamics of the COVID-19 pandemic in Nagasaki Prefecture, based on the number of machi-level daily cases. Furthermore, the findings in different waves can serve as references for subsequent pandemic prevention and control. This method helps the health authorities track and investigate outbreaks of COVID-19 that are specific to these environments, especially in rural areas where healthcare resources are scarce. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13690-022-00921-3. BioMed Central 2022-07-26 /pmc/articles/PMC9315091/ /pubmed/35883103 http://dx.doi.org/10.1186/s13690-022-00921-3 Text en © The Author(s) 2022 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Lu, Yixiao
Cai, Guoxi
Hu, Zhijian
He, Fei
Jiang, Yixian
Aoyagi, Kiyoshi
Exploring spatiotemporal patterns of COVID-19 infection in Nagasaki Prefecture in Japan using prospective space-time scan statistics from April 2020 to April 2022
title Exploring spatiotemporal patterns of COVID-19 infection in Nagasaki Prefecture in Japan using prospective space-time scan statistics from April 2020 to April 2022
title_full Exploring spatiotemporal patterns of COVID-19 infection in Nagasaki Prefecture in Japan using prospective space-time scan statistics from April 2020 to April 2022
title_fullStr Exploring spatiotemporal patterns of COVID-19 infection in Nagasaki Prefecture in Japan using prospective space-time scan statistics from April 2020 to April 2022
title_full_unstemmed Exploring spatiotemporal patterns of COVID-19 infection in Nagasaki Prefecture in Japan using prospective space-time scan statistics from April 2020 to April 2022
title_short Exploring spatiotemporal patterns of COVID-19 infection in Nagasaki Prefecture in Japan using prospective space-time scan statistics from April 2020 to April 2022
title_sort exploring spatiotemporal patterns of covid-19 infection in nagasaki prefecture in japan using prospective space-time scan statistics from april 2020 to april 2022
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9315091/
https://www.ncbi.nlm.nih.gov/pubmed/35883103
http://dx.doi.org/10.1186/s13690-022-00921-3
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