Spatio-temporal evolution and influencing factors of COVID-19 epidemic in Zhejiang Province

ABSTRACT

The global outbreak of novel Coronavirus Disease (COVID-19) epidemic has seriously endangered people's health and hindered rapid economic development. Geographic analysis of spatial and temporal transmission patterns in key regions can help prevent and control the epidemic. This paper takes Zhejiang province as the research area. With the help of POI data, the methods such as textual analysis, mathematical statistics, and spatial regression analysis are used to analyze the socio-demographic characteristics of confirmed cases and the spatio-temporal evolution of the epidemic, and then analyze its influencing factors. The results show that (1) The age distribution of confirmed cases spanned a wide range, showing normal distribution of "large in the middle and small at both ends." (2) The epidemic period is divided into five stages the initial period, the outbreak period, the steady decline period, the internal stable period, and the oversea input period. The interval between the onset time and announcing a confirmed case was mostly 0-6 d, and the time interval of non-local cases is longer than that of local cases, and the onset of most of the non-local cases occur on the day the patients leave their original place. There was no significant gender difference in the proportion of daily incidence, and the proportion of age had stage features. (3) The spatial distribution aligned in the direction of "Southeast-Northwest", the evolution trend developed from "single place distribution" to "multi-area cluster cases" and then to "key input" evolution, with "high-high" "high-low" clustering characteristics;The migration path of confirmed cases presented an obvious core-edge structure, and the first significant flow was from the center of Wuhan. (4) By analyzing the factors affecting the distribution of the epidemic,it is found that the ratio of the elderly population, per capita GDP, the proportion of the tertiary industry, the number of industries above the scale, and the distance from Wuhan were the dominant factors. Finally, several suggestions on targeted prevention and control measures are made, and the weaknesses of the study and future directions of efforts are pointed out.