利用2020年4月至2022年4月的前瞻性时空扫描统计数据探讨日本长崎县COVID-19感染的时空格局

Yixiao Lu, Guoxi Cai, Zhijian Hu, Fei He, Yixian Jiang, Kiyoshi Aoyagi
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引用次数: 1

摘要

背景:截至2022年4月,日本共发生6波2019冠状病毒病(COVID-19)感染。随着疫情的持续增长,发现COVID-19聚集性病例对于分配卫生资源和大幅改善决策至关重要。本研究旨在对长崎县新型冠状病毒肺炎(COVID-19)的活跃聚集性进行识别,形成不同感染时期高危地区的时空格局。方法:采用前瞻性时空扫描统计方法检测长崎县2020年4月1日至2022年4月7日连续5个时间段的新冠肺炎聚集性,并对其相对风险进行检测。结果:2020年12月以来,长崎市人口稠密区仍是受影响最严重的地区。每波疫情早期的大多数确诊病例都有到其他县旅行的历史。从城市地区到农村地区和偏远岛屿的空间集群的快速扩展表明了社区一级的传播。此外,福利设施和学校的疫情可能导致长崎县农村地区出现新的群集。结论:本研究基于机器级每日病例数,对长崎县COVID-19大流行的传播动态进行了全面分析。此外,不同波的研究结果可为后续的大流行防控提供参考。这种方法有助于卫生当局跟踪和调查这些环境中特定的COVID-19疫情,特别是在医疗资源匮乏的农村地区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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

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

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 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.

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