Abstract
To analyze the spatio-temporal aggregation of COVID-19 in mainland China within 20 days after the closure of Wuhan city, and provide a theoretical basis for formulating scientific prevention measures in similar major public health events in the future. Draw a distribution map of the cumulative number of COVID-19 by inverse distance weighted interpolation; analyze the spatio-temporal characteristics of the daily number of COVID-19 in mainland China by spatio-temporal autocorrelation analysis; use the spatio-temporal scanning statistics to detect the spatio-temporal clustering area of the daily number of new diagnosed cases. The cumulative number of diagnosed cases obeyed the characteristics of geographical proximity and network proximity to Hubei. Hubei and its neighboring provinces were most affected, and the impact in the eastern China was more dramatic than the impact in the western; the global spatio-temporal Moran’s I index showed an overall downward trend. Since the 10th day of the closure of Wuhan, the epidemic in China had been under effective control, and more provinces had shifted into low-incidence areas. The number of new diagnosed cases had gradually decreased, showing a random distribution in time and space (P< 0.1), and no clusters were formed. Conclusion: the spread of COVID-19 had obvious spatial-temporal aggregation. China’s experience shows that isolation city strategy can greatly contain the spread of the COVID-19 epidemic.
Highlights
COVID-19 is an infectious disease whose main symptoms were breathing, coughing and sneezing
This study focuses on the spatio-temporal distribution of COVID-19 in mainland China when the epidemic just broke out
The spatial distribution characteristics of the cumulative number of diagnosed cases with COVID-19 in mainland China on January 23 and February 11 are analyzed by inverse distance weighted interpolation, and the distribution map is drawn
Summary
COVID-19 is an infectious disease whose main symptoms were breathing, coughing and sneezing. By December 29, 2021, the cumulative number of diagnosed cases worldwide has exceeded 280 million, and the cumulative number of deaths has exceeded 5 m illion[2] It took only 2 or 3 months from the outbreak of COVID-19 to containment in mainland China. L iu[17] assesses the spread of the epidemic in Henan province through spatial autocorrelation analysis and relative risk coefficients. Jian[18] describes the spatial pattern and distribution characteristics of the epidemic situation in Henan province from the perspective of planning. These studies have achieved important results, explaining the epidemic mechanism of COVID-19 in time and space. This study uses spatio-temporal autocorrelation analysis and spatio-temporal scanning statistical methods to detect the spatio-temporal aggregation of COVID-19 and provide a theoretical basis for scientifically formulating epidemic prevention measures
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