Spatial distribution characteristics of the COVID-19 pandemic in Beijing and its relationship with environmental factors

Abstract Investigating the spatial distribution characteristics of the coronavirus disease 2019 (COVID-19) and exploring the influence of environmental factors that drive it is the basis for formulating rational and efficient prevention and control countermeasures. Therefore, this study aims to analyze the spatial distribution characteristics of COVID-19 pandemic in Beijing and its relationship with the environmental factors. Based on the incidences of new local COVID-19 cases in Beijing from June 11 to July 5, the spatial clustering characteristics of the COVID-19 pandemic in Beijing was investigated using spatial autocorrelation analysis. The relation between COVID-19 cases and environmental factors was assessed using the Spearman correlation analysis. Finally, geographically weighted regression (GWR) was applied to explore the influence of environmental factors on the spatial distribution of COVID-19 cases. The results showed that the development of COVID-19 pandemic in Beijing from June 11 to July 5 could be divided into two stages. The first stage was the outward expansion from June 11 to June 21, and the second stage (from June 22 to July 5) was the growth of the transmission in areas with existing previous cases. In addition, there was a ring of low value clusters around the Xinfadi market. This area was the key area for prevention and control. Population density and distance to Xinfadi market were the most critical factors that explained the pandemic development. The findings of this study can provide useful information for the global fighting against COVID-19.