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Fractional Model and Numerical Algorithms for Predicting COVID-19 with Isolation and Quarantine Strategies
In December 2019, a new outbreak in Wuhan, China has attracted world-wide attention, the virus then spread rapidly in most countries of the world, the objective of this paper is to investigate the mathematical modelling and dynamics of a novel coronavirus (COVID-19) with Caputo-Fabrizio fractional d...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer India
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8241535/ https://www.ncbi.nlm.nih.gov/pubmed/34226872 http://dx.doi.org/10.1007/s40819-021-01086-3 |
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author | Alla Hamou, Abdelouahed Azroul, Elhoussine Lamrani Alaoui, Abdelilah |
author_facet | Alla Hamou, Abdelouahed Azroul, Elhoussine Lamrani Alaoui, Abdelilah |
author_sort | Alla Hamou, Abdelouahed |
collection | PubMed |
description | In December 2019, a new outbreak in Wuhan, China has attracted world-wide attention, the virus then spread rapidly in most countries of the world, the objective of this paper is to investigate the mathematical modelling and dynamics of a novel coronavirus (COVID-19) with Caputo-Fabrizio fractional derivative in the presence of quarantine and isolation strategies. The existence and uniqueness of the solutions for the fractional model is proved using fixed point iterations, the fractional model are shown to have disease-free and an endemic equilibrium point.We construct a fractional version of the four-steps Adams-Bashforth method as well as the error estimate of this method. We have used this method to determine the numerical scheme of this model and Matlab program to illustrate the evolution of the virus in some countries (Morocco, Qatar, Brazil and Mexico) as well as to support theoretical results. The Least squares fitting is a way to find the best fit curve or line for a set of points, so we apply this method in this paper to construct an algorithm to estimate the parameters of fractional model as well as the fractional order, this model gives an estimate better than that of classical model. |
format | Online Article Text |
id | pubmed-8241535 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer India |
record_format | MEDLINE/PubMed |
spelling | pubmed-82415352021-07-01 Fractional Model and Numerical Algorithms for Predicting COVID-19 with Isolation and Quarantine Strategies Alla Hamou, Abdelouahed Azroul, Elhoussine Lamrani Alaoui, Abdelilah Int J Appl Comput Math Original Paper In December 2019, a new outbreak in Wuhan, China has attracted world-wide attention, the virus then spread rapidly in most countries of the world, the objective of this paper is to investigate the mathematical modelling and dynamics of a novel coronavirus (COVID-19) with Caputo-Fabrizio fractional derivative in the presence of quarantine and isolation strategies. The existence and uniqueness of the solutions for the fractional model is proved using fixed point iterations, the fractional model are shown to have disease-free and an endemic equilibrium point.We construct a fractional version of the four-steps Adams-Bashforth method as well as the error estimate of this method. We have used this method to determine the numerical scheme of this model and Matlab program to illustrate the evolution of the virus in some countries (Morocco, Qatar, Brazil and Mexico) as well as to support theoretical results. The Least squares fitting is a way to find the best fit curve or line for a set of points, so we apply this method in this paper to construct an algorithm to estimate the parameters of fractional model as well as the fractional order, this model gives an estimate better than that of classical model. Springer India 2021-06-30 2021 /pmc/articles/PMC8241535/ /pubmed/34226872 http://dx.doi.org/10.1007/s40819-021-01086-3 Text en © The Author(s), under exclusive licence to Springer Nature India Private Limited 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Paper Alla Hamou, Abdelouahed Azroul, Elhoussine Lamrani Alaoui, Abdelilah Fractional Model and Numerical Algorithms for Predicting COVID-19 with Isolation and Quarantine Strategies |
title | Fractional Model and Numerical Algorithms for Predicting COVID-19 with Isolation and Quarantine Strategies |
title_full | Fractional Model and Numerical Algorithms for Predicting COVID-19 with Isolation and Quarantine Strategies |
title_fullStr | Fractional Model and Numerical Algorithms for Predicting COVID-19 with Isolation and Quarantine Strategies |
title_full_unstemmed | Fractional Model and Numerical Algorithms for Predicting COVID-19 with Isolation and Quarantine Strategies |
title_short | Fractional Model and Numerical Algorithms for Predicting COVID-19 with Isolation and Quarantine Strategies |
title_sort | fractional model and numerical algorithms for predicting covid-19 with isolation and quarantine strategies |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8241535/ https://www.ncbi.nlm.nih.gov/pubmed/34226872 http://dx.doi.org/10.1007/s40819-021-01086-3 |
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