tetano
Editor, Senior Moderator
Arch Public Health
. 2022 Jul 26;80(1):176.
doi: 10.1186/s13690-022-00921-3.
Exploring spatiotemporal patterns of COVID-19 infection in Nagasaki Prefecture in Japan using prospective space-time scan statistics from April 2020 to April 2022
Yixiao Lu[SUP] #[/SUP][SUP] 1 [/SUP], Guoxi Cai[SUP] #[/SUP][SUP] 1 2 3 [/SUP], Zhijian Hu[SUP] 4 [/SUP], Fei He[SUP] 5 [/SUP], Yixian Jiang[SUP] 4 [/SUP], Kiyoshi Aoyagi[SUP] 1 [/SUP]
Affiliations
Abstract
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.
Keywords: COVID-19; Disease surveillance; Emerging clusters; SaTScan; Space-time pattern.
. 2022 Jul 26;80(1):176.
doi: 10.1186/s13690-022-00921-3.
Exploring spatiotemporal patterns of COVID-19 infection in Nagasaki Prefecture in Japan using prospective space-time scan statistics from April 2020 to April 2022
Yixiao Lu[SUP] #[/SUP][SUP] 1 [/SUP], Guoxi Cai[SUP] #[/SUP][SUP] 1 2 3 [/SUP], Zhijian Hu[SUP] 4 [/SUP], Fei He[SUP] 5 [/SUP], Yixian Jiang[SUP] 4 [/SUP], Kiyoshi Aoyagi[SUP] 1 [/SUP]
Affiliations
- PMID: 35883103
- DOI: 10.1186/s13690-022-00921-3
Abstract
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.
Keywords: COVID-19; Disease surveillance; Emerging clusters; SaTScan; Space-time pattern.