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Mechanisms of recurrent outbreak of COVID-19: a model-based study.
Han, Chuanliang; Li, Meijia; Haihambo, Naem; Babuna, Pius; Liu, Qingfang; Zhao, Xixi; Jaeger, Carlo; Li, Ying; Yang, Saini.
  • Han C; State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875 China.
  • Li M; Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, 1050 Brussels, Belgium.
  • Haihambo N; Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, 1050 Brussels, Belgium.
  • Babuna P; School of Environment, Beijing Normal University, Beijing, 100875 China.
  • Liu Q; Department of Geography and Environmental Science, The University of Reading, Whiteknights, Reading, RG6 6AB UK.
  • Zhao X; Colledge of Agriculture and Natural Resources, Kwame Nkrumah University of Science and Technology, PMB KNUST, Kumasi, Ghana.
  • Jaeger C; Department of Psychology, The Ohio State University, Columbus, OH 43210 USA.
  • Li Y; Beijing Anding Hospital, Capital Medical University, Beijing, 100088 China.
  • Yang S; The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, 100088 China.
Nonlinear Dyn ; 106(2): 1169-1185, 2021.
Article en En | MEDLINE | ID: mdl-33758464
Recurrent outbreaks of the coronavirus disease 2019 (COVID-19) have occurred in many countries around the world. We developed a twofold framework in this study, which is composed by one novel descriptive model to depict the recurrent global outbreaks of COVID-19 and one dynamic model to understand the intrinsic mechanisms of recurrent outbreaks. We used publicly available data of cumulative infected cases from 1 January 2020 to 2 January 2021 in 30 provinces in China and 43 other countries around the world for model validation and further analyses. These time series data could be well fitted by the new descriptive model. Through this quantitative approach, we discovered two main mechanisms that strongly correlate with the extent of the recurrent outbreak: the sudden increase in cases imported from overseas and the relaxation of local government epidemic prevention policies. The compartmental dynamical model (Susceptible, Exposed, Infectious, Dead and Recovered (SEIDR) Model) could reproduce the obvious recurrent outbreak of the epidemics and showed that both imported infected cases and the relaxation of government policies have a causal effect on the emergence of a new wave of outbreak, along with variations in the temperature index. Meanwhile, recurrent outbreaks affect consumer confidence and have a significant influence on GDP. These results support the necessity of policies such as travel bans, testing of people upon entry, and consistency of government prevention and control policies in avoiding future waves of epidemics and protecting economy.
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