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Stability analysis and simulation of the novel Corornavirus mathematical model via the Caputo fractional-order derivative: A case study of Algeria

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 CO...

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Autores principales: Moussa, Yacine El hadj, Boudaoui, Ahmed, Ullah, Saif, Bozkurt, Fatma, Abdeljawad, Thabet, Alqudah, Manar A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier B.V. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8141347/
https://www.ncbi.nlm.nih.gov/pubmed/34055583
http://dx.doi.org/10.1016/j.rinp.2021.104324
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author Moussa, Yacine El hadj
Boudaoui, Ahmed
Ullah, Saif
Bozkurt, Fatma
Abdeljawad, Thabet
Alqudah, Manar A.
author_facet Moussa, Yacine El hadj
Boudaoui, Ahmed
Ullah, Saif
Bozkurt, Fatma
Abdeljawad, Thabet
Alqudah, Manar A.
author_sort Moussa, Yacine El hadj
collection PubMed
description 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.
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spelling pubmed-81413472021-05-24 Stability analysis and simulation of the novel Corornavirus mathematical model via the Caputo fractional-order derivative: A case study of Algeria Moussa, Yacine El hadj Boudaoui, Ahmed Ullah, Saif Bozkurt, Fatma Abdeljawad, Thabet Alqudah, Manar A. Results Phys Article 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. The Authors. Published by Elsevier B.V. 2021-07 2021-05-23 /pmc/articles/PMC8141347/ /pubmed/34055583 http://dx.doi.org/10.1016/j.rinp.2021.104324 Text en © 2021 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Moussa, Yacine El hadj
Boudaoui, Ahmed
Ullah, Saif
Bozkurt, Fatma
Abdeljawad, Thabet
Alqudah, Manar A.
Stability analysis and simulation of the novel Corornavirus mathematical model via the Caputo fractional-order derivative: A case study of Algeria
title Stability analysis and simulation of the novel Corornavirus mathematical model via the Caputo fractional-order derivative: A case study of Algeria
title_full Stability analysis and simulation of the novel Corornavirus mathematical model via the Caputo fractional-order derivative: A case study of Algeria
title_fullStr Stability analysis and simulation of the novel Corornavirus mathematical model via the Caputo fractional-order derivative: A case study of Algeria
title_full_unstemmed Stability analysis and simulation of the novel Corornavirus mathematical model via the Caputo fractional-order derivative: A case study of Algeria
title_short Stability analysis and simulation of the novel Corornavirus mathematical model via the Caputo fractional-order derivative: A case study of Algeria
title_sort stability analysis and simulation of the novel corornavirus mathematical model via the caputo fractional-order derivative: a case study of algeria
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8141347/
https://www.ncbi.nlm.nih.gov/pubmed/34055583
http://dx.doi.org/10.1016/j.rinp.2021.104324
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