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A Fractional Order Covid-19 Epidemic Model with Mittag–Leffler Kernel

We consider a nonlinear fractional-order Covid-19 model in a sense of the Atagana–Baleanu fractional derivative used for the analytic and computational studies. The model consists of six classes of persons, including susceptible, protected susceptible, asymptomatic infected, symptomatic infected, qu...

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Detalles Bibliográficos
Autores principales: Khan, H., Ibrahim, M., Khan, A., Tunç, O., Abdeljawad, Th.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10156573/
http://dx.doi.org/10.1007/s10958-023-06417-x
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author Khan, H.
Ibrahim, M.
Khan, A.
Tunç, O.
Abdeljawad, Th.
author_facet Khan, H.
Ibrahim, M.
Khan, A.
Tunç, O.
Abdeljawad, Th.
author_sort Khan, H.
collection PubMed
description We consider a nonlinear fractional-order Covid-19 model in a sense of the Atagana–Baleanu fractional derivative used for the analytic and computational studies. The model consists of six classes of persons, including susceptible, protected susceptible, asymptomatic infected, symptomatic infected, quarantined, and recovered individuals. The model is studied for the existence of solution with the help of a successive iterative technique with limit point as the solution of the model. The Hyers–Ulam stability is also studied. A numerical scheme is proposed and tested on the basis of the available literature. The graphical results predict the curtail of spread within the next 5000 days. Moreover, there is a gradual increase in the population of protected susceptible individuals.
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spelling pubmed-101565732023-05-09 A Fractional Order Covid-19 Epidemic Model with Mittag–Leffler Kernel Khan, H. Ibrahim, M. Khan, A. Tunç, O. Abdeljawad, Th. J Math Sci Article We consider a nonlinear fractional-order Covid-19 model in a sense of the Atagana–Baleanu fractional derivative used for the analytic and computational studies. The model consists of six classes of persons, including susceptible, protected susceptible, asymptomatic infected, symptomatic infected, quarantined, and recovered individuals. The model is studied for the existence of solution with the help of a successive iterative technique with limit point as the solution of the model. The Hyers–Ulam stability is also studied. A numerical scheme is proposed and tested on the basis of the available literature. The graphical results predict the curtail of spread within the next 5000 days. Moreover, there is a gradual increase in the population of protected susceptible individuals. Springer International Publishing 2023-05-04 2023 /pmc/articles/PMC10156573/ http://dx.doi.org/10.1007/s10958-023-06417-x Text en © Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. 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 Article
Khan, H.
Ibrahim, M.
Khan, A.
Tunç, O.
Abdeljawad, Th.
A Fractional Order Covid-19 Epidemic Model with Mittag–Leffler Kernel
title A Fractional Order Covid-19 Epidemic Model with Mittag–Leffler Kernel
title_full A Fractional Order Covid-19 Epidemic Model with Mittag–Leffler Kernel
title_fullStr A Fractional Order Covid-19 Epidemic Model with Mittag–Leffler Kernel
title_full_unstemmed A Fractional Order Covid-19 Epidemic Model with Mittag–Leffler Kernel
title_short A Fractional Order Covid-19 Epidemic Model with Mittag–Leffler Kernel
title_sort fractional order covid-19 epidemic model with mittag–leffler kernel
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10156573/
http://dx.doi.org/10.1007/s10958-023-06417-x
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