Skip to content
Communications in Mathematical Biology and Neuroscience ISSN 2052-2541

Archives › Volume 2023 (2023)

Commun. Math. Biol. Neurosci. 2023 (2023), Article ID 88

Stability analysis of SLIVR COVID-19 epidemic model with quarantine policy

Youssra Hajri, EL Mehdi Farah, Amina Allali, Saida Amine

PDF (409.9 KB) https://doi.org/10.28919/cmbn/8092

Abstract

In this paper, we present a mathematical model illustrating the dynamics of the COVID-19 disease with vaccination and quarantine strategies. The presented model contains five equations that describe the interaction between individuals who are susceptible, exposed, infected, vaccinated, and recovered. We start the study by verifying the positivity and boundedness of solutions. The existence and the stability of both disease-free equilibrium and endemic equilibrium are proved. Finally, numerical simulations are performed to demonstrate the behavior of the infection over time and to say the influence of quarantine and vaccination on both the COVID-19 dynamics and the basic reproduction number mathcalR0 for controlling the disease’s spread.

Published
21 August 2023
Volume
2023 (2023)
License
CC BY 3.0

Copyright © 2023 Youssra Hajri, EL Mehdi Farah, Amina Allali, Saida Amine. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Cite this article

Y. Hajri, E. M. Farah, A. Allali, S. Amine, Stability analysis of SLIVR COVID-19 epidemic model with quarantine policy, Commun. Math. Biol. Neurosci. 2023 (2023), 88. https://doi.org/10.28919/cmbn/8092

BibTeX
@article{Hajri2023,
  author  = {Hajri, Youssra and Farah, EL Mehdi and Allali, Amina and Amine, Saida},
  title   = {Stability analysis of SLIVR COVID-19 epidemic model with quarantine policy},
  journal = {Commun. Math. Biol. Neurosci.},
  volume  = {2023},
  year    = {2023},
  pages   = {88},
  doi     = {10.28919/cmbn/8092}
}