Journal of Shandong University (Health Sciences) ›› 2020, Vol. 58 ›› Issue (10): 82-88.doi: 10.6040/j.issn.1671-7554.0.2020.0735

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Clustering distribution of COVID-19 in Wenzhou from January to March 2020 based on spatiotemporal analysis

LIU Lili, JIA Yan, QI Chang, ZHU Yuchen, LI Chunyu, SHE Kaili, LIU Tingxuan, LI Xiujun   

  1. Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China
  • Published:2020-10-08

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Abstract: Objective To explore the spatiotemporal distribution of COVID-19 in Wenzhou and to provide theoretical basis for the formulation of preventive and control measures. Methods The epidemic data of COVID-19 cases returning from Wuhan and local secondary cases who contacted with the confirmed cases from 21 January 2020 to 1 March 2020 were collected and analyzed. ArcGIS 10.5 was used to produce a map of the number of cases. Spatiotemporal clustering analysis was performed with SaTScan 9.6 to explore the epidemic characteristics of returning and local cases and to investigate the causes of local cases. Results As of 1 March 2020, the cumulative number of COVID-19 cases was 504, with an incidence of 6.08/100 000. The cumulative number of discharged cases was 447. Of all cases, 168 returned from Wuhan and 221 local secondary cases contacted with the confirmed cases. The spatial-temporal cluster analysis of the two types of cases showed obvious clustering, and the clustering results were basically consistent. Clusters occurred mainly in Yueqing City, Ruian City and Yongjia County. Conclusion There is a spatialtemporal aggregation of COVID-19 in Wenzhou. Counties with more COVID-19 cases returning from Wuhan had more local secondary cases. Prevention and control measures should be taken especially in regions where a large number of people migrated to reduce the risk of COVID-19.

Key words: Coronavirus disease 2019, Spatiotemporal clustering, Spatial analysis, Space epidemiology, Wenzhou City

CLC Number: 

  • R574
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