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

Guoqing Zhi; Bin Meng; Hui Lin; Xin Zhang; Min Xu; Siyu Chen; Juan Wang

doi:10.3389/fpubh.2023.1293888

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

Front Public Health. 2024 Jan 4:11:1293888. doi: 10.3389/fpubh.2023.1293888. eCollection 2023.

Authors

Guoqing Zhi^{1

2

3}, Bin Meng^{3

4}, Hui Lin^{1

2}, Xin Zhang⁵, Min Xu⁵, Siyu Chen^{4

6

7}, Juan Wang^{3

4}

Affiliations

¹ Electronic Science Research Institute of China Electronics Technology Group Corporation, Beijing, China.
² National Engineering Laboratory for Public Security Risk Perception and Control by Big Data, Beijing, China.
³ College of Applied Arts and Sciences, Beijing Union University, Beijing, China.
⁴ Laboratory of Urban Cultural Sensing & Computing, Beijing Union University, Beijing, China.
⁵ Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China.
⁶ Southwest United University Campus, Yunnan Normal University, Kunming, China.
⁷ The Engineering Research Center of GIS Technology in Western China of Ministry of Education of China, Kunming, China.

Abstract

Introduction: COVID-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.

Methods: Through 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.

Results: Our 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.

Discussion: Despite 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.

Keywords: COVID-19; China; Geodetector, Wuhan; co-location; spatial risk; urban facilities.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

COVID-19* / epidemiology
China / epidemiology
Cities
Communicable Diseases* / epidemiology
Epidemics*
Humans

Grants and funding

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).