JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE) ›› 2020, Vol. 40 ›› Issue (06): 713-718.doi: 10.3969/j.issn.1674-8115.2020.06.003

• Novel coronavirus article • Previous Articles     Next Articles

Retrospective analysis of Chinese epidemic situation model based on elbow cluster analysis

LI Qiang1, 2, SUN Zhe2, QIAN Bi-yun2, 3, FENG Tie-nan2, 4   

  1. 1. Shanghai Jiao University School of Public Health, Shanghai 200025, China; 2. Clinical Research Institute, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; 3. Clinical Research Promotion and Development Center, Shanghai Shenkang Hospital Development Center, Shanghai 200041, China; 4. Second Affiliated Hospital of Chengdu Medical College, China National Nuclear Corporation 416 Hospital, Chengdu 610057, China
  • Online:2020-06-28 Published:2020-06-28
  • Supported by:
    Medical Engineering Cross Project of Shanghai Jiao Tong University (YG2017QN70); Technology Transfer Project of Science and Technology Department of Shanghai Jiao Tong University School of Medicine (ZT201919).

Abstract: Objective · To explore the correlation patterns of the new coronavirus disease 2019 (COVID-19) epidemic in various provincial administrative regions in China at the early stage of the epidemic, and forecast the following development of epidemic situation. Methods · The data on the COVID-19 epidemic situation in various provincial administrative regions in China published by National Health Commission of People's Republic of China from Jan. 13 to Feb. 13, 2020, were retrospectively analyzed. The elbow cluster analysis method was used to cluster the provincial administrative regions. The SEIR (susceptible-exposed-infectious-recovered) model was used to calculate the basic infection number (R0) of different clusters, whose changing trends were also predicted. Results · According to the prevalence rates, the 34 provincial administrative regions were divided into four types of clusters: Cluster Ⅰ (22 provincial administrative regions) , Cluster Ⅱ (9 provincial administrative regions), Cluster Ⅲ (2 provincial administrative regions) and Cluster Ⅳ (Hubei). The prevalence rate of Hubei was higher than those of other clusters (P=0.000), but the differences in the cure rate and the case-fatality rate among the four clusters were not statistically significant; the R0 values based on the SEIR model of them were 2.764, 3.056, 3.899 and 3.984, respectively. By Feb. 13, 2020, except for Hubei, the cumulative prevalence curves of the other clusters tended to be stable and the cure rates increased. The prevalence rate and case-fatality rate of Hubei were still higher, and the cure rate was lower. Conclusion · From Jan. 13 to Feb. 13, 2020, 34 provincial administrative regions in China can be divided into four clusters according to the severity of the COVID-19 epidemic, and the prevalence rate of Cluster Ⅳ was significantly higher than those of other three clusters; by Feb. 13, 2020, the epidemic situations in the Cluster Ⅰ , Ⅱ and Ⅲ has been alleviated, and the epidemic situation in Cluster Ⅳ areas were still severe.

Key words: coronavirus disease 2019 (COVID-19), elbow cluster analysis, SEIR (susceptible-exposed-infectious-recovered) model, retrospective analysis

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