Stability analysis and simulation of the novel Corornavirus mathematical model via the Caputo fractional-order derivative: A case study of Algeria.
COVID-19
Lyapunov function
Real data
Simulations
Stability analysis
Journal
Results in physics
ISSN: 2211-3797
Titre abrégé: Results Phys
Pays: Netherlands
ID NLM: 101731363
Informations de publication
Date de publication:
Jul 2021
Jul 2021
Historique:
received:
23
03
2021
revised:
09
05
2021
accepted:
10
05
2021
pubmed:
1
6
2021
medline:
1
6
2021
entrez:
31
5
2021
Statut:
ppublish
Résumé
The novel coronavirus infectious disease (or COVID-19) almost spread widely around the world and causes a huge panic in the human population. To explore the complex dynamics of this novel infection, several mathematical epidemic models have been adopted and simulated using the statistical data of COVID-19 in various regions. In this paper, we present a new nonlinear fractional order model in the Caputo sense to analyze and simulate the dynamics of this viral disease with a case study of Algeria. Initially, after the model formulation, we utilize the well-known least square approach to estimate the model parameters from the reported COVID-19 cases in Algeria for a selected period of time. We perform the existence and uniqueness of the model solution which are proved via the Picard-Lindelöf method. We further compute the basic reproduction numbers and equilibrium points, then we explore the local and global stability of both the disease-free equilibrium point and the endemic equilibrium point. Finally, numerical results and graphical simulation are given to demonstrate the impact of various model parameters and fractional order on the disease dynamics and control.
Identifiants
pubmed: 34055583
doi: 10.1016/j.rinp.2021.104324
pii: S2211-3797(21)00453-8
pmc: PMC8141347
doi:
Types de publication
Journal Article
Langues
eng
Pagination
104324Informations de copyright
© 2021 The Authors.
Déclaration de conflit d'intérêts
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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