广东省COVID-19疫情时空聚集特征及影响因素分析

Analysis of Spatio-Temporal Clustering Characteristics and Influencing Factors of COVID-19 Epidemic in Guangdong Province

摘要: COVID-19在县级尺度内的病例时间变化与空间聚集特征及其影响因素在疫情防控工作中起到重要作用。本文尝试以县级尺度为单位，收集2020年1月26日至3月1日广东省确诊病例信息，采用空间自相关分析法、因子分析法、多元线性回归分析法等，探究广东省疫情在时空上的变化特征，并揭示其影响因素。结果表明，广东疫情特征主要表现为：时间上分为四个主要阶段即上升期、高发期、下降期、低水平波动期；空间上，病例呈现较强的空间聚集性且聚集强度逐渐增强，热点区县主要分布在东莞、广州、深圳市、佛山、中山、清远等地市；疫情情况与人口流动规模、客运量、人均GDP和限额以上餐饮业餐费收入显著相关。

Abstract: The temporal variation and spatial clustering characteristics of COVID-19 cases at the county level and its influencing factors play an important role in epidemic prevention and control. This paper attempts to collect the information of confirmed cases on January 26, 2020 and March 1, 2020 in Guangdong Province at the county level. Spatial autocorrelation analysis, factor analysis, multiple linear regression analysis and other methods are used to explore the spatiotemporal variation characteristics of the epidemic in Guangdong Province and reveal its influencing factors. The results showed that the characteristics of the epidemic in Guangdong were as follows: the time of the epidemic was divided into four main stages, namely, rising period, high incidence period, declining period and low level fluctuation period. In terms of spatial distribution, cases showed strong spatial clustering and the intensity of clustering gradually increased. Hotspot areas were mainly distributed in Dongguan, Guangzhou, Shenzhen, Foshan, Zhongshan, Qingyuan and other cities. The epidemic situation is significantly related to population flow scale, passenger volume, per capita GDP and meal income of restaurants above designated size.