Spatial Aggregation and Spatial-Temporal Pattern of Provincial Cumulative Confirmed Count of Novel Coronavirus Pneumonia (COVID-19) in China/ 中国各省新型冠状病毒肺炎累计确诊人数的空间聚集及时空格局演变分析

Novel coronavirus pneumonia (COVID-19) spreads quickly We need to have an accurate understanding of the cumulative confirmed count in various provinces in China The static spatial distribution and dynamic evolution of the cumulative confirmed count in various provinces in China are revealed by using spatial statistical analysis The data of the cumulative confirmed count from January 26th, 2020 to February 20th, 2020, from the outbreak to the control of the virus, is analyzed The results show the cumulative confirmed count of each province in China has a positive spatial correlation before February 3th, a negative spatial correlation from February 3th to February 11th, and a random distribution in space after February 11th Looking at the characteristics of local aggregation in different provinces, the high-low clustering occurs mainly in Hubei, while the low-high clustering mainly in provinces around Hubei And provinces far from Hubei are low-low pattern And the provinces with significant high-low clustering and low-high clustering gradually increase