Han Yi, Yang Lan, Jia Kun, Li Jie, Feng Siyuan, Chen Wei, Zhao Wenwu, Pereira Paulo
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
College of Geoscience and Surveying engineering, China University of Mining &Technology, Beijing 100083, China.
Sci Total Environ. 2021 Mar 20;761:144257. doi: 10.1016/j.scitotenv.2020.144257. Epub 2020 Dec 10.
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.
研究2019冠状病毒病（COVID-19）的空间分布特征并探究驱动其传播的环境因素的影响，是制定合理高效防控对策的基础。因此，本研究旨在分析北京市COVID-19疫情的空间分布特征及其与环境因素的关系。基于北京市6月11日至7月5日本地新增COVID-19病例的发病情况，采用空间自相关分析方法研究了北京市COVID-19疫情的空间聚集特征。利用Spearman相关分析评估了COVID-19病例与环境因素之间的关系。最后，应用地理加权回归（GWR）方法探究环境因素对COVID-19病例空间分布的影响。结果表明，北京市6月11日至7月5日COVID-19疫情的发展可分为两个阶段。第一阶段是6月11日至6月21日的向外扩散阶段，第二阶段（6月22日至7月5日）是已有病例地区传播的增长阶段。此外，新发地市场周围存在一个低值聚集环。该区域是防控的重点区域。人口密度和与新发地市场的距离是解释疫情发展的最关键因素。本研究结果可为全球抗击COVID-19提供有用信息。
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