病毒学报

探讨重庆地区COVID-19疫情时空分布特征及扩散模式,以期未来为本地应对公共卫生应急事件积累经验。本文收集重庆市卫生健康委员会公布的官方数据,采用ArcGIS 10.2软件进行空间计量分析,并实现区域分布可视化,描述性统计和社会因素相关分析采用SPSS 20.0和Graphpad Prism 7.0软件进行统计和作图。结果 5个时间节点,重庆地区COVID-19累计报告发病率的Moran's I值均为正值(均P<0.05);局部Getis-ord G_i~*指数分析探测到渝东北高渝东南低的态势越发明显;标准差椭圆展布呈现东北-西南的空间格局,随时间的变化经历了扩散-极化-扩散-稳定的过程;重心走势呈现向西南(渝西片区)移动距离逐渐减弱态势,市内出行(r=0.449,P=0.007)和交通网络(r_s=0.321,P=0.049)对COVID-19的流行具有正相关性。重庆地区COVID-19疫情存在空间聚集性,高发聚集区域集中在渝东北片区,GIS较好地揭示了疫情聚集性变化过程和传播的时空趋势,市内出行和交通网络2个社会因素对重庆地区疫情影响较大。

We wished to explore the time and space distribution characteristics of coronavirus disease 2019(COVID-19) in Chongqing,China. In this way,we accumulated experience for a local response to publichealth emergencies in the future. Official data released by the Chongqing Municipal Health Commission were collected. ArcGIS 10.2 was used for spatial-measurement analyses,and visualization of regional distribution was realized. Descriptive statistics and social-factor correlation analyses were carried out by SPSS v20.0(IBM).Prism 7.0(GraphPad)was employed for counting and figure creation. As a result,Moran′s I values for the cumulative incidence of COVID-19 in Chongqing were positive(P < 0.05 for all)within five time nodes. The local Getis-ord Gi*showed that the COVID-19 incidence in northeast Chongqing was high,the COVID-19 incidence in southeast Chongqing was low,and that the trend was becoming increasingly obvious. The standarddeviation ellipse presented a spatial pattern in the northeast→southwest direction,and passed through diffusion– polarization – diffusion – stability as time progresses. COVID-19 transmission in Chongqing followed a pattern. The center of the epidemic moved gradually towards the south west(western Chongqing). City travel(r = 0.449,P = 0.007)and the traffic network(r_s = 0.321,P = 0.049)were positively related to COVID-19 prevalence. There was spatial clustering of COVID-19 in Chongqing,and a high incidence of COVID-19 was concentrated in northeast Chongqing. These data suggest that geographic-information systems could be applied to reveal the spatial-clustering changes and spreading trends of COVID-19 in Chongqing. Two social factors(city travel and the traffic network)had an impact on the prevalence of COVID-19 in Chongqing.