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Date of Publication:2020-01-01

Journal:Zhongguo Gonglu Xuebao/China Journal of Highway and Transport

Volume:33

Issue:11

Page Number:43-54

ISSN No.:1001-7372

Abstract:This study explores how traffic exposure and land use patterns affect the spread of coronavirus disease 2019 (COVID-19) at the community level. Using the data collected from 1 947 confirmed COVID-19 cases and 315 neighborhoods in A City, this study applied geocodes, kernel density estimation, spatial statistics, and network analysis approaches to obtain 14 indicators related to traffic exposure and land use in a 500 m buffer for each confirmed community. Data from the road network, public transit network, points of interest (POI), and the spatial distribution of national gross domestic product and population in a 1 km×1 km grid in 2015 were used. A classical global Poisson regression model and a geographically weighted Poisson regression model with variable coefficients were adapted to estimate the complex relationships between traffic exposure variables (road network density, facility proximity), land use variables (mixture, intensity), and the spread of COVID-19 at the community level. The results show that the geographically weighted Poisson regression model obtains a better result when the spatial heterogeneity of traffic exposure variables and land use variables is considered. Despite this, road density, public transit density, building density, population density, central business district (CBD) proximity, and land value have a positive impact on the spread of COVID-19 at the community level. However, entrance (exit) proximity, green park proximity, and land use mixture have both positive and negative effects on the spread of COVID-19, and the spatial effects vary significantly. The effects of population density, land value, green park proximity, and land use mixture on the spread of COVID-19 are much higher than those of other variables. This study illustrates that urban space elements have an impact on both communicable and noncommunicable diseases. These findings provide insight for controlling the outbreak of an epidemic in the context of transportation planning and land use. © 2020, Editorial Department of China Journal of Highway and Transport. All right reserved.

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