文献类型：期刊文献

英文题名：Spatial co-location patterns between early COVID-19 risk and urban facilities: a case study of Wuhan, China

作者：Zhi, Guoqing[1,2,3];Meng, Bin[3,4];Lin, Hui[1,2];Zhang, Xin[5];Xu, Min[5];Chen, Siyu[4,6,7];Wang, Juan[3,4]

第一作者：Zhi, Guoqing

通讯作者：Meng, B[1];Meng, B[2]

机构：[1]China Elect Technol Grp Corp, Elect Sci Res Inst, Beijing, Peoples R China;[2]Natl Engn Lab Publ Secur Risk Percept & Control Bi, Beijing, Peoples R China;[3]Beijing Union Univ, Coll Appl Arts & Sci, Beijing, Peoples R China;[4]Beijing Union Univ, Lab Urban Cultural Sensing & Comp, Beijing, Peoples R China;[5]Chinese Acad Sci, Aerosp Informat Res Inst, Beijing, Peoples R China;[6]Yunnan Normal Univ, Southwest United Univ Campus, Kunming, Peoples R China;[7]Minist Educ China, Engn Res Ctr GIS Technol Western China, Kunming, Peoples R China

第一机构：China Elect Technol Grp Corp, Elect Sci Res Inst, Beijing, Peoples R China

通讯机构：[1]corresponding author), Beijing Union Univ, Coll Appl Arts & Sci, Beijing, Peoples R China;[2]corresponding author), Beijing Union Univ, Lab Urban Cultural Sensing & Comp, Beijing, Peoples R China.|[11417]北京联合大学;[114172]北京联合大学应用文理学院;

年份：2024

卷号：11

外文期刊名：FRONTIERS IN PUBLIC HEALTH

收录：;WOS:【SSCI(收录号:WOS:001143658600001)，SCI-EXPANDED(收录号:WOS:001143658600001)】；

基金：We are grateful to the Electronic Science Research Institute of China Electronics Technology Group Corporation and Aerospace Information Research Institute (AIR), Chinese Academy of Sciences for providing data and resource support, and to Beijing Union University for providing innovations in ideas and analytical methods.r The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by National Natural Science Foundation of China, under grant number 41671165; National Key Research and Development Program under grant number 2022YFC0869800; R&D Program of Beijing Municipal Education Commission under grant number KM202211417015; the Academic Research Projects of Beijing Union University (No. ZKZD202305).

语种：英文

外文关键词：COVID-19; spatial risk; co-location; urban facilities; Geodetector, Wuhan; China

摘要：IntroductionCOVID-19, being a new type of infectious disease, holds significant implications for scientific prevention and control to understand its spatiotemporal transmission process. This study examines the diverse spatial patterns of COVID-19 within Wuhan by analyzing early case data alongside urban infrastructure information.MethodsThrough co-location analysis, we assess both local and global spatial risks linked to the epidemic. In addition, we use the Geodetector, identifying facilities displaying unique spatial risk characteristics, revealing factors contributing to heightened risk.ResultsOur findings unveil a noticeable spatial distribution of COVID-19 in the city, notably influenced by road networks and functional zones. Higher risk levels are observed in the central city compared to its outskirts. Specific facilities such as parking, residence, ATM, bank, entertainment, and hospital consistently exhibit connections with COVID-19 case sites. Conversely, facilities like subway station, dessert restaurant, and movie theater display a stronger association with case sites as distance increases, hinting at their potential as outbreak focal points.DiscussionDespite our success in containing the recent COVID-19 outbreak, uncertainties persist regarding its origin and initial spread. Some experts caution that with increased human activity, similar outbreaks might become more frequent. This research provides a comprehensive analytical framework centered on urban facilities, contributing quantitatively to understanding their impact on the spatial risks linked with COVID-19 outbreaks. It enriches our understanding of the interconnectedness between urban facility distribution and transportation flow, affirming and refining the distance decay law governing infectious disease risks. Furthermore, the study offers practical guidance for post-epidemic urban planning, promoting the development of safer urban environments resilient to epidemics. It equips government bodies with a reliable quantitative analysis method for more accurately predicting and assessing infectious disease risks. In conclusion, this study furnishes both theoretical and empirical support for tailoring distinct strategies to prevent and control COVID-19 epidemics.