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A report on COVID-19 epidemic in Pakistan using SEIR fractional model
Recently, novel coronavirus is a serious global issue and having a negative impact on the economy of the whole world. Like other countries, it also effected the economy and people of Pakistan. According to the publicly reported data, the first case of novel corona virus in Pakistan was reported on 2...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7747742/ https://www.ncbi.nlm.nih.gov/pubmed/33335284 http://dx.doi.org/10.1038/s41598-020-79405-9 |
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author | Ahmad, Zubair Arif, Muhammad Ali, Farhad Khan, Ilyas Nisar, Kottakkaran Sooppy |
author_facet | Ahmad, Zubair Arif, Muhammad Ali, Farhad Khan, Ilyas Nisar, Kottakkaran Sooppy |
author_sort | Ahmad, Zubair |
collection | PubMed |
description | Recently, novel coronavirus is a serious global issue and having a negative impact on the economy of the whole world. Like other countries, it also effected the economy and people of Pakistan. According to the publicly reported data, the first case of novel corona virus in Pakistan was reported on 27th February 2020. The aim of the present study is to describe the mathematical model and dynamics of COVID-19 in Pakistan. To investigate the spread of coronavirus in Pakistan, we develop the SEIR time fractional model with newly, developed fractional operator of Atangana–Baleanu. We present briefly the analysis of the given model and discuss its applications using world health organization (WHO) reported data for Pakistan. We consider the available infection cases from 19th March 2020, till 31st March 2020 and accordingly, various parameters are fitted or estimated. It is worth noting that we have calculated the basic reproduction number [Formula: see text] which shows that virus is spreading rapidly. Furthermore, stability analysis of the model at disease free equilibrium DFE and endemic equilibriums EE is performed to observe the dynamics and transmission of the model. Finally, the AB fractional model is solved numerically. To show the effect of the various embedded parameters like fractional parameter [Formula: see text] on the model, various graphs are plotted. It is worth noting that the base of our investigation, we have predicted the spread of disease for next 200 days. |
format | Online Article Text |
id | pubmed-7747742 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-77477422020-12-22 A report on COVID-19 epidemic in Pakistan using SEIR fractional model Ahmad, Zubair Arif, Muhammad Ali, Farhad Khan, Ilyas Nisar, Kottakkaran Sooppy Sci Rep Article Recently, novel coronavirus is a serious global issue and having a negative impact on the economy of the whole world. Like other countries, it also effected the economy and people of Pakistan. According to the publicly reported data, the first case of novel corona virus in Pakistan was reported on 27th February 2020. The aim of the present study is to describe the mathematical model and dynamics of COVID-19 in Pakistan. To investigate the spread of coronavirus in Pakistan, we develop the SEIR time fractional model with newly, developed fractional operator of Atangana–Baleanu. We present briefly the analysis of the given model and discuss its applications using world health organization (WHO) reported data for Pakistan. We consider the available infection cases from 19th March 2020, till 31st March 2020 and accordingly, various parameters are fitted or estimated. It is worth noting that we have calculated the basic reproduction number [Formula: see text] which shows that virus is spreading rapidly. Furthermore, stability analysis of the model at disease free equilibrium DFE and endemic equilibriums EE is performed to observe the dynamics and transmission of the model. Finally, the AB fractional model is solved numerically. To show the effect of the various embedded parameters like fractional parameter [Formula: see text] on the model, various graphs are plotted. It is worth noting that the base of our investigation, we have predicted the spread of disease for next 200 days. Nature Publishing Group UK 2020-12-17 /pmc/articles/PMC7747742/ /pubmed/33335284 http://dx.doi.org/10.1038/s41598-020-79405-9 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ahmad, Zubair Arif, Muhammad Ali, Farhad Khan, Ilyas Nisar, Kottakkaran Sooppy A report on COVID-19 epidemic in Pakistan using SEIR fractional model |
title | A report on COVID-19 epidemic in Pakistan using SEIR fractional model |
title_full | A report on COVID-19 epidemic in Pakistan using SEIR fractional model |
title_fullStr | A report on COVID-19 epidemic in Pakistan using SEIR fractional model |
title_full_unstemmed | A report on COVID-19 epidemic in Pakistan using SEIR fractional model |
title_short | A report on COVID-19 epidemic in Pakistan using SEIR fractional model |
title_sort | report on covid-19 epidemic in pakistan using seir fractional model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7747742/ https://www.ncbi.nlm.nih.gov/pubmed/33335284 http://dx.doi.org/10.1038/s41598-020-79405-9 |
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