Built environment and early infection of COVID-19 in urban districts: A case study of Huangzhou

Bo Li,You Peng,He He,Mingshu Wang,Tao Feng

doi:10.1016/j.scs.2020.102685

Abstract

Since COVID-19 spread rapidly worldwide, many countries have experienced significant growth in the number of confirmed cases and deaths. Earlier studies have examined various factors that may contribute to the contagion rate of COVID-19, such as air pollution, smoking, humidity, and temperature. As there is a lack of studies at the neighborhood-level detailing the spatial settings of built environment attributes, this study explored the variations in the size of the COVID-19 confirmed case clusters across the urban district Huangzhou in the city of Huanggang. Clusters of infectious cases in the initial outbreak of COVID-19 were identified geographically through GIS methods. The hypothetic relationships between built environment attributes and clusters of COVID-19 cases have been investigated with the structural equation model. The results show the statistically significant direct and indirect influences of commercial vitality and transportation infrastructure on the number of confirmed cases in an infectious cluster. The clues ch inducing a high risk of contagions have been evidenced and provided for the decision-making practice responding to the initial stage of possible severe epidemics, indicating that the local public health authorities should implement sufficient measures and adopt effective interventions in the areas and places with a high probability of crowded residents.

Highlights

Since the initial cases of the ’unknown pneumonia’ reported in Wuhan, China, in December 2019 (Guan et al, 2020; Lu, Stratton, & Tang, 2020), such an infectious disease has an outbreak and rapidly spread all over the world (Wei, Wang, & Kraak, 2020)
Using data of the built environment around confirmed cases, we investigated the relationships between the quantity of assembled COVID-19 confirmed cases and the built environment attributes of corresponding neighborhood-level urban space
The anonymized COVID-19 confirmed cases at the initial stage of the outbreak from 21 January 2020 to 18 February 2020 were transformed into the spatial point on the map of Huangzhou district through ArcGIS

Summary

Introduction

Since the initial cases of the ’unknown pneumonia’ reported in Wuhan, China, in December 2019 (Guan et al, 2020; Lu, Stratton, & Tang, 2020), such an infectious disease has an outbreak and rapidly spread all over the world (Wei, Wang, & Kraak, 2020). The objec tive of this investigation is to provide evidence regarding the potential risk of COVID-19 spreading and clustering related to the conceptualized constructs regarding urban commercial development, medical service capacity, and transportation infrastructure. The point-of-interests (POIs) of various types of commercial facilities and medical services, road network lengths, building density, and average housing price at the community level, which is surrounding the clusters (within 1000 m buffer), are incorpo rated into the distributions map of COVID-19 infected cases with ArcGIS. We explored the relationships between infected cases clustering and fine-scale built environment attributes

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