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A fractional order SITR mathematical model for forecasting of transmission of COVID-19 of India with lockdown effect
In this paper, we consider a mathematical model to explain, understanding, and to forecast the outbreaks of COVID-19 in India. The model has four components leading to a system of fractional order differential equations incorporating the refuge concept to study the lockdown effect in controlling COV...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985659/ https://www.ncbi.nlm.nih.gov/pubmed/33777667 http://dx.doi.org/10.1016/j.rinp.2021.104067 |
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author | Askar, S.S. Ghosh, Dipankar Santra, P.K. Elsadany, Abdelalim A. Mahapatra, G.S. |
author_facet | Askar, S.S. Ghosh, Dipankar Santra, P.K. Elsadany, Abdelalim A. Mahapatra, G.S. |
author_sort | Askar, S.S. |
collection | PubMed |
description | In this paper, we consider a mathematical model to explain, understanding, and to forecast the outbreaks of COVID-19 in India. The model has four components leading to a system of fractional order differential equations incorporating the refuge concept to study the lockdown effect in controlling COVID-19 spread in India. We investigate the model using the concept of Caputo fractional-order derivative. The goal of this model is to estimate the number of total infected, active cases, deaths, as well as recoveries from COVID-19 to control or minimize the above issues in India. The existence, uniqueness, non-negativity, and boundedness of the solutions are established. In addition, the local and global asymptotic stability of the equilibrium points of the fractional-order system and the basic reproduction number are studied for understanding and prediction of the transmission of COVID-19 in India. The next step is to carry out sensitivity analysis to find out which parameter is the most dominant to affect the disease’s endemicity. The results reveal that the parameters [Formula: see text] and [Formula: see text] are the most dominant sensitivity indices towards the basic reproductive number. A numerical illustration is presented via computer simulations using MATLAB to show a realistic point of view. |
format | Online Article Text |
id | pubmed-7985659 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Author(s). Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79856592021-03-23 A fractional order SITR mathematical model for forecasting of transmission of COVID-19 of India with lockdown effect Askar, S.S. Ghosh, Dipankar Santra, P.K. Elsadany, Abdelalim A. Mahapatra, G.S. Results Phys Article In this paper, we consider a mathematical model to explain, understanding, and to forecast the outbreaks of COVID-19 in India. The model has four components leading to a system of fractional order differential equations incorporating the refuge concept to study the lockdown effect in controlling COVID-19 spread in India. We investigate the model using the concept of Caputo fractional-order derivative. The goal of this model is to estimate the number of total infected, active cases, deaths, as well as recoveries from COVID-19 to control or minimize the above issues in India. The existence, uniqueness, non-negativity, and boundedness of the solutions are established. In addition, the local and global asymptotic stability of the equilibrium points of the fractional-order system and the basic reproduction number are studied for understanding and prediction of the transmission of COVID-19 in India. The next step is to carry out sensitivity analysis to find out which parameter is the most dominant to affect the disease’s endemicity. The results reveal that the parameters [Formula: see text] and [Formula: see text] are the most dominant sensitivity indices towards the basic reproductive number. A numerical illustration is presented via computer simulations using MATLAB to show a realistic point of view. The Author(s). Published by Elsevier B.V. 2021-05 2021-03-23 /pmc/articles/PMC7985659/ /pubmed/33777667 http://dx.doi.org/10.1016/j.rinp.2021.104067 Text en © 2021 The Author(s) 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 Askar, S.S. Ghosh, Dipankar Santra, P.K. Elsadany, Abdelalim A. Mahapatra, G.S. A fractional order SITR mathematical model for forecasting of transmission of COVID-19 of India with lockdown effect |
title | A fractional order SITR mathematical model for forecasting of transmission of COVID-19 of India with lockdown effect |
title_full | A fractional order SITR mathematical model for forecasting of transmission of COVID-19 of India with lockdown effect |
title_fullStr | A fractional order SITR mathematical model for forecasting of transmission of COVID-19 of India with lockdown effect |
title_full_unstemmed | A fractional order SITR mathematical model for forecasting of transmission of COVID-19 of India with lockdown effect |
title_short | A fractional order SITR mathematical model for forecasting of transmission of COVID-19 of India with lockdown effect |
title_sort | fractional order sitr mathematical model for forecasting of transmission of covid-19 of india with lockdown effect |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985659/ https://www.ncbi.nlm.nih.gov/pubmed/33777667 http://dx.doi.org/10.1016/j.rinp.2021.104067 |
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