College of Environment and Planning, Henan University, Kaifeng 475004, China; Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Region, Henan University, Kaifeng 475004, China.
College of Environment and Planning, Henan University, Kaifeng 475004, China; Key Research Institute of Yellow River Civilization and Sustainable Development, Henan University, Kaifeng 475001, China; Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Region, Henan University, Kaifeng 475004, China.
Sci Total Environ. 2020 Nov 20;744:140929. doi: 10.1016/j.scitotenv.2020.140929. Epub 2020 Jul 14.
This paper uses the exploratory spatial data analysis and the geodetector method to analyze the spatial and temporal differentiation characteristics and the influencing factors of the COVID-19 (corona virus disease 2019) epidemic spread in mainland China based on the cumulative confirmed cases, average temperature, and socio-economic data. The results show that: (1) the epidemic spread rapidly from January 24 to February 20, 2020, and the distribution of the epidemic areas tended to be stable over time. The epidemic spread rate in Hubei province, in its surrounding, and in some economically developed cities was higher, while that in western part of China and in remote areas of central and eastern China was lower. (2) The global and local spatial correlation characteristics of the epidemic distribution present a positive correlation. Specifically, the global spatial correlation characteristics experienced a change process from agglomeration to decentralization. The local spatial correlation characteristics were mainly composed of the'high-high' and 'low-low' clustering types, and the situation of the contiguous layout was very significant. (3) The population inflow from Wuhan and the strength of economic connection were the main factors affecting the epidemic spread, together with the population distribution, transport accessibility, average temperature, and medical facilities, which affected the epidemic spread to varying degrees. (4) The detection factors interacted mainly through the mutual enhancement and nonlinear enhancement, and their influence on the epidemic spread rate exceeded that of single factors. Besides, each detection factor has an interval range that is conducive to the epidemic spread.
本文利用探索性空间数据分析和地理探测器方法,基于累计确诊病例、平均气温和社会经济数据,分析了中国大陆 COVID-19(2019 年冠状病毒病)疫情传播的时空分异特征及其影响因素。结果表明:(1)疫情于 2020 年 1 月 24 日至 2 月 20 日快速扩散,疫区分布随时间趋于稳定。湖北省及其周边地区以及部分经济发达城市的疫情传播速度较高,而中国西部和中东部偏远地区的疫情传播速度较低。(2)疫情分布的全局和局部空间相关特征呈正相关。具体而言,全局空间相关特征经历了从集聚到分散的变化过程。局部空间相关特征主要由“高高”和“低低”聚类类型组成,且连续布局的情况非常显著。(3)武汉的人口流入和经济联系强度是影响疫情传播的主要因素,人口分布、交通可达性、平均气温和医疗设施也对疫情传播产生了不同程度的影响。(4)检测因素主要通过相互增强和非线性增强相互作用,其对疫情传播率的影响超过了单一因素。此外,每个检测因素都有一个有利于疫情传播的区间范围。