Computer Science ›› 2021, Vol. 48 ›› Issue (6A): 196-202.doi: 10.11896/jsjkx.201100086

• Big Data & Data Science • Previous Articles     Next Articles

Research on Propagation of COVID-19 Based on Multiple Models

LIU Han-qing1, KANG Xiao-dong1, GAO Wan-chun2, LI Bo1,3, WANG Ya-ge1, ZHANG Hua-li1, BAI Fang1   

  1. 1 School of Medical Image Science,Tianjin Medical University,Tianjin 300202,China
    2 Qianjiang Central Hospital Affiliated of Jishou University,Chongqing 409000,China
    3 Tianjin Third Central Hospital,Tianjin 300170,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:LIU Han-qing,born in 1997,M.S.candidate.His main research interest is medical image processing.
    GAO Wan-chun,born in 1963,associate chief physician.His main research interest is medical imaging technology.
  • Supported by:
    Beijing-Tianjin-Hebei Collaborative Innovation Project(17YEXTZC00020).

Abstract: The propagation of COVID-19 to all provinces and cities across the country in a short period of time has not only severely affected people's normal life and social economy,but also threatened people's lives.Therefore,multi-model COVID-19 transmission research has clear theories and realistic significance.This study is based on public data.First,the small-world and scale-free network models are used to study node propagation control.Secondly,the improved SEIR model is used in conjunction with the Wuhan epidemic trend to divide the infected into symptomatic and asymptomatic infections.The hospitalization and death states are joined,andsimulation studies under three conditions are carried out:normal social behavior,social behavior to keep a distance,and social behavior of isolation measures,respectively.Finally,the level and periodicity of COVID-19 infection are analyzed based on the chaos model.The data simulation results verify that the above model has good applicability.

Key words: Chaos model, COVID-19, Scale-free network, SEIR, Small world network

CLC Number: 

  • TP391
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