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Modeling the dynamics of the novel coronavirus using Caputo-Fabrizio derivative

The virus that begins from Wuhan China, known as COVID-19 or coronavirus is still a huge panic for humans around the globe. The elimination of this virus from our society needs proper attentions to follows the rule suggested by World Health Organization (WHO). A vast literature on the modeling of th...

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Autores principales: Alzahrani, Ebraheem, El-Dessoky, M.M., Baleanu, Dumitru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7969849/
http://dx.doi.org/10.1016/j.aej.2021.03.028
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author Alzahrani, Ebraheem
El-Dessoky, M.M.
Baleanu, Dumitru
author_facet Alzahrani, Ebraheem
El-Dessoky, M.M.
Baleanu, Dumitru
author_sort Alzahrani, Ebraheem
collection PubMed
description The virus that begins from Wuhan China, known as COVID-19 or coronavirus is still a huge panic for humans around the globe. The elimination of this virus from our society needs proper attentions to follows the rule suggested by World Health Organization (WHO). A vast literature on the modeling of this infection in various perspective is available. In the present work, we design a new mathematical model for COVID-19 pandemic by utilizing the real infected cases reported from Kingdom of Saudi Arabia. Initially, we formulate the model with the help of classical integer order nonlinear differential equations. The treatment class is considered the model to analyze the impact of treatment on the disease dynamics. The Caputo-Fabrizio derivative with the non-singular exponential kernel is applied in order to reformulate the proposed COVID-19 transmission model with a fractional order. The biologically important parameter called the basic reproductive number is investigated both theoretically and numerically. The estimated values of [Formula: see text] for the selected period are approximated to be [Formula: see text]. Further, by making use of the Picard Lindelöf theorem we provide the existence and uniqueness of the COVID-19 fractional epidemic model. Moreover, the fractional model is solved numerically and a number of simulation results are depicted using the real estimated parameters. The impact of various model parameters and memory index are shown graphically. We conclude that the fractional order epidemic models are more appropriate and provide deep insights into the disease dynamics.
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spelling pubmed-79698492021-03-18 Modeling the dynamics of the novel coronavirus using Caputo-Fabrizio derivative Alzahrani, Ebraheem El-Dessoky, M.M. Baleanu, Dumitru Alexandria Engineering Journal Article The virus that begins from Wuhan China, known as COVID-19 or coronavirus is still a huge panic for humans around the globe. The elimination of this virus from our society needs proper attentions to follows the rule suggested by World Health Organization (WHO). A vast literature on the modeling of this infection in various perspective is available. In the present work, we design a new mathematical model for COVID-19 pandemic by utilizing the real infected cases reported from Kingdom of Saudi Arabia. Initially, we formulate the model with the help of classical integer order nonlinear differential equations. The treatment class is considered the model to analyze the impact of treatment on the disease dynamics. The Caputo-Fabrizio derivative with the non-singular exponential kernel is applied in order to reformulate the proposed COVID-19 transmission model with a fractional order. The biologically important parameter called the basic reproductive number is investigated both theoretically and numerically. The estimated values of [Formula: see text] for the selected period are approximated to be [Formula: see text]. Further, by making use of the Picard Lindelöf theorem we provide the existence and uniqueness of the COVID-19 fractional epidemic model. Moreover, the fractional model is solved numerically and a number of simulation results are depicted using the real estimated parameters. The impact of various model parameters and memory index are shown graphically. We conclude that the fractional order epidemic models are more appropriate and provide deep insights into the disease dynamics. THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. 2021-10 2021-03-18 /pmc/articles/PMC7969849/ http://dx.doi.org/10.1016/j.aej.2021.03.028 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
Alzahrani, Ebraheem
El-Dessoky, M.M.
Baleanu, Dumitru
Modeling the dynamics of the novel coronavirus using Caputo-Fabrizio derivative
title Modeling the dynamics of the novel coronavirus using Caputo-Fabrizio derivative
title_full Modeling the dynamics of the novel coronavirus using Caputo-Fabrizio derivative
title_fullStr Modeling the dynamics of the novel coronavirus using Caputo-Fabrizio derivative
title_full_unstemmed Modeling the dynamics of the novel coronavirus using Caputo-Fabrizio derivative
title_short Modeling the dynamics of the novel coronavirus using Caputo-Fabrizio derivative
title_sort modeling the dynamics of the novel coronavirus using caputo-fabrizio derivative
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7969849/
http://dx.doi.org/10.1016/j.aej.2021.03.028
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