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. 2022 Oct:129:103932.
doi: 10.1016/j.cities.2022.103932. Epub 2022 Aug 12.

Correlations between the urban built environmental factors and the spatial distribution at the community level in the reported COVID-19 samples: A case study of Wuhan

Jingwei Wang  1 , Fanbo Zeng  2 , Haida Tang  3   4 , Junjie Wang  3   4 , Lihua Xing  5
Affiliations

Correlations between the urban built environmental factors and the spatial distribution at the community level in the reported COVID-19 samples: A case study of Wuhan

Jingwei Wang et al. Cities. 2022 Oct.

Abstract

COVID-19 has dramatically changed the lifestyle of people, especially in urban environments. This paper investigated the variations of built environments that were measurably associated with the spread of COVID-19 in 150 Wuhan communities. The incidence rate in each community before and after the lockdown (January 23, 2020), as respective dependent variables, represented the situation under normal circumstances and non-pharmaceutical interventions (NPI). After controlling the population density, floor area ratio (FAR), property age and sociodemographic factors, the built environmental factors in two spatial dimensions, the 15-minute walking life circle and the 10-minute cycling life circle, were brought into the Hierarchical Linear Regression Model and the Ridge Regression Model. The results indicated that before lockdown, the number of markets and schools were positively associated with the incidence rate, while community population density and FAR were negatively associated with COVID-19 transmission. After lockdown, FAR, GDP, the number of hospitals (in the 15-minute walking life circle) and the bus stations (in the 10-minute cycling life circle) became negatively correlated with the incidence rate, while markets remained positive. This study effectively extends the discussions on the association between the urban built environment and the spread of COVID-19. Meanwhile, given the limitations of sociodemographic data sources, the conclusions of this study should be interpreted and applied with caution.

Keywords: Built environmental factors; COVID-19 spatial analysis; Community level; Hierarchical Linear Regression; Ridge regression.

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Conflict of interest statement

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, and there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled “Correlations between the urban built environmental factors and the spatial distribution at the community level in the reported COVID-19 samples: A case study of Wuhan”.

Figures

Fig. 1
Fig. 1
Incidence rates (‱) of 150 communities in Wuhan on 12 February 2020 (Incidence 2).
Fig. 2
Fig. 2
Sketch map of the two types of life circles of one community and the spatial distribution of hospitals.
Fig. 3
Fig. 3
Pearson correlations of factors in 15-minute walking life circle (* p < 0.05. ** p < 0.01.).
Fig. 4
Fig. 4
Pearson correlations of factors in 10-minute cycling life circle (* p < 0.05. ** p < 0.01.).
Fig. A.1
Fig. A.1
Ridge Trace for the 15-minute walking life circle in Phase 1 (Model 5) (k = 0.3).
Fig. A.2
Fig. A.2
Ridge Trace for the 15-minute walking life circle in Phase 2 (Model 6) (k = 0.2).
Fig. A.3
Fig. A.3
Ridge Trace for the 10-minute cycling life circle in Phase 1 (Model 7) (k = 0.3).
Fig. A.4
Fig. A.4
Ridge Trace for the 10-minute cycling life circle in Phase 2 (Model 8) (k = 0.3).
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