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Vaccination control of an epidemic model with time delay and its application to COVID-19.
Zhai, Shidong; Luo, Guoqiang; Huang, Tao; Wang, Xin; Tao, Junli; Zhou, Ping.
  • Zhai S; School of Automation, Chongqing University of Posts and Telecommunications, Chongqing, 400065 China.
  • Luo G; School of Automation, Chongqing University of Posts and Telecommunications, Chongqing, 400065 China.
  • Huang T; School of Automation, Chongqing University of Posts and Telecommunications, Chongqing, 400065 China.
  • Wang X; School of Automation, Chongqing University of Posts and Telecommunications, Chongqing, 400065 China.
  • Tao J; Chongqing University Cancer Hospital, Chongqing, 400030 China.
  • Zhou P; School of Science, Chongqing University of Posts and Telecommunications, Chongqing, 400065 China.
Nonlinear Dyn ; 106(2): 1279-1292, 2021.
Article in English | MEDLINE | ID: covidwho-1252178
ABSTRACT
This paper studies an SEIR-type epidemic model with time delay and vaccination control. The vaccination control is applied when the basic reproduction number R 0 > 1 . The vaccination strategy is expressed as a state delayed feedback which is related to the current and previous state of the epidemic model, and makes the model become a linear system in new coordinates. For the presence and absence of vaccination control, we investigate the nonnegativity and boundedness of the model, respectively. We obtain some sufficient conditions for the eigenvalues of the linear system such that the nonnegativity of the epidemic model can be guaranteed when the vaccination strategy is applied. In addition, we study the stability of disease-free equilibrium when R 0 < 1 and the persistent of disease when R 0 > 1 . Finally, we use the obtained theoretical results to simulate the vaccination strategy to control the spread of COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Topics: Vaccines Language: English Journal: Nonlinear Dyn Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Topics: Vaccines Language: English Journal: Nonlinear Dyn Year: 2021 Document Type: Article