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Dynamic behaviors and non-instantaneous impulsive vaccination of an SAIQR model on complex networks

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  • Fu, Xinjie
  • Wang, JinRong

Abstract

We establish an SAIQR epidemic network model, in which asymptomatic infected people (A) are as contagious as infected people (I). The basic reproductive number R0 is calculated, and the globally asymptotically stable of the disease-free equilibrium, the globally attractive and globally asymptotically stable of the endemic equilibrium are obtained. For the control of epidemic transmission, we take into account the non-instantaneous impulsive vaccination in the model, calculate the basic reproduction number R0⁎ of the model, and demonstrate that the disease-free T-periodic solution is globally attractive and the model is permanent. Finally, we choose scale-free network to simulate numerically and validate the results of this paper.

Suggested Citation

  • Fu, Xinjie & Wang, JinRong, 2024. "Dynamic behaviors and non-instantaneous impulsive vaccination of an SAIQR model on complex networks," Applied Mathematics and Computation, Elsevier, vol. 465(C).
    • Handle: RePEc:eee:apmaco:v:465:y:2024:i:c:s0096300323005945
    DOI: 10.1016/j.amc.2023.128425
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    References listed on IDEAS

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    1. Gourieroux, C. & Jasiak, J., 2023. "Time varying Markov process with partially observed aggregate data: An application to coronavirus," Journal of Econometrics, Elsevier, vol. 232(1), pages 35-51.
    2. Jiao, Jianjun & Cai, Shaohong & Li, Limei, 2016. "Impulsive vaccination and dispersal on dynamics of an SIR epidemic model with restricting infected individuals boarding transports," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 145-159.
    3. Huang, He & Xu, Yang & Xing, Jingli & Shi, Tianyu, 2023. "Social influence or risk perception? A mathematical model of self-protection against asymptomatic infection in multilayer network," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    4. Cheng, Xinxin & Wang, Yi & Huang, Gang, 2021. "Global dynamics of a network-based SIQS epidemic model with nonmonotone incidence rate," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    5. Sarkar, Kankan & Khajanchi, Subhas & Nieto, Juan J., 2020. "Modeling and forecasting the COVID-19 pandemic in India," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    6. Xia Liu & Kun Zhao & Junli Wang & Huatao Chen, 2022. "Stability Analysis Of A Seiqrs Epidemic Model On The Finite Scale-Free Network," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 30(02), pages 1-13, March.
    7. Yang, Peng & Wang, Yuanshi, 2019. "Dynamics for an SEIRS epidemic model with time delay on a scale-free network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
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