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Mathematical modeling and analysis of COVID-19: A study of new variant Omicron
We construct a new mathematical model to better understand the novel coronavirus (omicron variant). We briefly present the modeling of COVID-19 with the omicron variant and present their mathematical results. We study that the Omicron model is locally asymptotically stable if the basic reproduction...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9040451/ https://www.ncbi.nlm.nih.gov/pubmed/35498561 http://dx.doi.org/10.1016/j.physa.2022.127452 |
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author | Khan, Muhammad Altaf Atangana, Abdon |
author_facet | Khan, Muhammad Altaf Atangana, Abdon |
author_sort | Khan, Muhammad Altaf |
collection | PubMed |
description | We construct a new mathematical model to better understand the novel coronavirus (omicron variant). We briefly present the modeling of COVID-19 with the omicron variant and present their mathematical results. We study that the Omicron model is locally asymptotically stable if the basic reproduction number [Formula: see text] , while for [Formula: see text] , the model at the disease-free equilibrium is globally asymptotically stable. We extend the model to the second-order differential equations to study the possible occurrence of the layers(waves). We then extend the model to a fractional stochastic version and studied its numerical results. The real data for the period ranging from November 1, 2021, to January 23, 2022, from South Africa are considered to obtain the realistic values of the model parameters. The basic reproduction number for the suggested data is found to be approximate [Formula: see text] which is very close to the actual basic reproduction in South Africa. We perform the global sensitivity analysis using the PRCC method to investigate the most influential parameters that increase or decrease [Formula: see text]. We use the new numerical scheme recently reported for the solution of piecewise fractional differential equations to present the numerical simulation of the model. Some graphical results for the model with sensitive parameters are given which indicate that the infection in the population can be minimized by following the recommendations of the world health organizations (WHO), such as social distances, using facemasks, washing hands, avoiding gathering, etc. |
format | Online Article Text |
id | pubmed-9040451 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90404512022-04-26 Mathematical modeling and analysis of COVID-19: A study of new variant Omicron Khan, Muhammad Altaf Atangana, Abdon Physica A Article We construct a new mathematical model to better understand the novel coronavirus (omicron variant). We briefly present the modeling of COVID-19 with the omicron variant and present their mathematical results. We study that the Omicron model is locally asymptotically stable if the basic reproduction number [Formula: see text] , while for [Formula: see text] , the model at the disease-free equilibrium is globally asymptotically stable. We extend the model to the second-order differential equations to study the possible occurrence of the layers(waves). We then extend the model to a fractional stochastic version and studied its numerical results. The real data for the period ranging from November 1, 2021, to January 23, 2022, from South Africa are considered to obtain the realistic values of the model parameters. The basic reproduction number for the suggested data is found to be approximate [Formula: see text] which is very close to the actual basic reproduction in South Africa. We perform the global sensitivity analysis using the PRCC method to investigate the most influential parameters that increase or decrease [Formula: see text]. We use the new numerical scheme recently reported for the solution of piecewise fractional differential equations to present the numerical simulation of the model. Some graphical results for the model with sensitive parameters are given which indicate that the infection in the population can be minimized by following the recommendations of the world health organizations (WHO), such as social distances, using facemasks, washing hands, avoiding gathering, etc. Elsevier B.V. 2022-08-01 2022-04-26 /pmc/articles/PMC9040451/ /pubmed/35498561 http://dx.doi.org/10.1016/j.physa.2022.127452 Text en © 2022 Elsevier B.V. All rights reserved. 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 Khan, Muhammad Altaf Atangana, Abdon Mathematical modeling and analysis of COVID-19: A study of new variant Omicron |
title | Mathematical modeling and analysis of COVID-19: A study of new variant Omicron |
title_full | Mathematical modeling and analysis of COVID-19: A study of new variant Omicron |
title_fullStr | Mathematical modeling and analysis of COVID-19: A study of new variant Omicron |
title_full_unstemmed | Mathematical modeling and analysis of COVID-19: A study of new variant Omicron |
title_short | Mathematical modeling and analysis of COVID-19: A study of new variant Omicron |
title_sort | mathematical modeling and analysis of covid-19: a study of new variant omicron |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9040451/ https://www.ncbi.nlm.nih.gov/pubmed/35498561 http://dx.doi.org/10.1016/j.physa.2022.127452 |
work_keys_str_mv | AT khanmuhammadaltaf mathematicalmodelingandanalysisofcovid19astudyofnewvariantomicron AT atanganaabdon mathematicalmodelingandanalysisofcovid19astudyofnewvariantomicron |