Analysis of the spatial characteristics of the residential communities of COVID-19 cases based on GIS platform—Taking the central urban area of Wuhan as an example

Abstract

The COVID-19 pandemic is rampant around the world, dramatically increasing the number of infected people, and greatly affecting the lives of people living in central urban areas. In China, one of the cities most affected by COVID-19 is Wuhan, where the distribution of residential communities with COVID-19 cases is indicative of viral spread. Analyses of spatial characteristics and influencing factors in case communities in the central Wuhan urban area provide indicators for exploring the COVID-19 environmental epidemiology and urban planning. This study used ArcGIS technology and spatial analysis methods such as spatial autocorrelation analysis, kernel density estimation, standard deviation ellipse analysis, and near analysis to explore the spatial distribution data patterns in case communities in Wuhan. Results indicate that 73% of the case communities were located within 150 m of main roads, while 90% of the case communities were located within 220 m of urban roads. The clustered spatial distribution of the case communities indicates a multi-core cluster pattern along the Yangtze River, with northwest to southeast trend, large distribution differences, and prominent spatial imbalance. The transportation network is a significant agent of the spread of the epidemic. At the same time, green space, population density, and gross domestic product (GDP) show no significant effects on the spread of COVID-19. The results of this study can provide some references for basic epidemiological research and urban planning.