Associating COVID-19 Severity with Urban Factors: A Case Study of Wuhan

Xin Li, Lin Zhou, Tao Jia, Ran Peng, Xiongwu Fu and Yuliang Zou
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Xin Li: School of Architecture and Civil Engineering, Xiamen University, Xiamen 361005, China
Lin Zhou: School of Urban Design, Wuhan University, Wuhan 430072, China
Tao Jia: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
Ran Peng: School of Civil Engineering and Architecture, Wuhan Institute of Technology, Wuhan 430074, China
Xiongwu Fu: Information Department, Wuhan Land Use and Urban Spatial Planning Research Center, Wuhan 430010, China
Yuliang Zou: School of Health Sciences, Wuhan University, Wuhan 430071, China

IJERPH, 2020, vol. 17, issue 18, 1-20

Abstract: Wuhan encountered a serious attack in the first round of the coronavirus disease 2019 (COVID-19) pandemic, which has resulted in a public health social impact, including public mental health. Based on the Weibo help data, we inferred the spatial distribution pattern of the epidemic situation and its impacts. Seven urban factors, i.e., urban growth, general hospital, commercial facilities, subway station, land-use mixture, aging ratio, and road density, were selected for validation with the ordinary linear model, in which the former six factors presented a globally significant association with epidemic severity. Then, the geographically weighted regression model (GWR) was adopted to identify their unevenly distributed effects in the urban space. Among the six factors, the distribution and density of major hospitals exerted significant effects on epidemic situation. Commercial facilities appear to be the most prevalently distributed significant factor on epidemic situation over the city. Urban growth, in particular the newly developed residential quarters with high-rise buildings around the waterfront area of Hanyang and Wuchang, face greater risk of the distribution. The influence of subway stations concentrates at the adjacency place where the three towns meet and some near-terminal locations. The aging ratio of the community dominantly affects the hinterland of Hankou to a broader extent than other areas in the city. Upon discovering the result, a series of managerial implications that coordinate various urban factors were proposed. This research may contribute toward developing specific planning and design responses for different areas in the city based on a better understanding of the occurrence, transmission, and diffusion of the COVID-19 epidemic in the metropolitan area.

Keywords: COVID-19; Weibo data; epidemic analysis; urban spatial patterns; Wuhan (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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