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Stability of a delayed SARS-CoV-2 reactivation model with logistic growth and adaptive immune response

Author

Listed:
  • Elaiw, A.M.
  • Alsaedi, A.J.
  • Hobiny, A.D.
  • Aly, S.

Abstract

This paper develops and analyzes a SARS-CoV-2 dynamics model with logistic growth of healthy epithelial cells, CTL immune and humoral (antibody) immune responses. The model is incorporated with four mixed (distributed/discrete) time delays, delay in the formation of latent infected epithelial cells, delay in the formation of active infected epithelial cells, delay in the activation of latent infected epithelial cells, and maturation delay of new SARS-CoV-2 particles. We establish that the model’s solutions are non-negative and ultimately bounded. We deduce that the model has five steady states and their existence and stability are perfectly determined by four threshold parameters. We study the global stability of the model’s steady states using Lyapunov method. The analytical results are enhanced by numerical simulations. The impact of intracellular time delays on the dynamical behavior of the SARS-CoV-2 is addressed. We noted that increasing the time delay period can suppress the viral replication and control the infection. This could be helpful to create new drugs that extend the delay time period.

Suggested Citation

  • Elaiw, A.M. & Alsaedi, A.J. & Hobiny, A.D. & Aly, S., 2023. "Stability of a delayed SARS-CoV-2 reactivation model with logistic growth and adaptive immune response," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 616(C).
    • Handle: RePEc:eee:phsmap:v:616:y:2023:i:c:s0378437123001590
    DOI: 10.1016/j.physa.2023.128604
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    References listed on IDEAS

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    1. Qi, Kai & Jiang, Daqing & Hayat, Tasawar & Alsaedi, Ahmed, 2021. "Virus dynamic behavior of a stochastic HIV/AIDS infection model including two kinds of target cell infections and CTL immune responses," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 188(C), pages 548-570.
    2. Elaiw, A.M. & Al Agha, A.D., 2021. "Global dynamics of SARS-CoV-2/cancer model with immune responses," Applied Mathematics and Computation, Elsevier, vol. 408(C).
    3. Ahmed M. Elaiw & Abdullah J. Alsaedi & Afnan Diyab Al Agha & Aatef D. Hobiny, 2022. "Global Stability of a Humoral Immunity COVID-19 Model with Logistic Growth and Delays," Mathematics, MDPI, vol. 10(11), pages 1-28, May.
    4. Christine S.M. Currie & John W. Fowler & Kathy Kotiadis & Thomas Monks & Bhakti Stephan Onggo & Duncan A. Robertson & Antuela A. Tako, 2020. "How simulation modelling can help reduce the impact of COVID-19," Journal of Simulation, Taylor & Francis Journals, vol. 14(2), pages 83-97, April.
    5. Sabbar, Yassine & Kiouach, Driss & Rajasekar, S.P. & El-idrissi, Salim El Azami, 2022. "The influence of quadratic Lévy noise on the dynamic of an SIC contagious illness model: New framework, critical comparison and an application to COVID-19 (SARS-CoV-2) case," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    6. S. P. Rajasekar & M. Pitchaimani & Quanxin Zhu & Kaibo Shi, 2021. "Exploring the Stochastic Host-Pathogen Tuberculosis Model with Adaptive Immune Response," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-23, June.
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