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A fractional order epidemic model for the simulation of outbreaks of Ebola
The Ebola outbreak in 2014 caused many infections and deaths. Some literature works have proposed some models to study Ebola virus, such as SIR, SIS, SEIR, etc. It is proved that the fractional order model can describe epidemic dynamics better than the integer order model. In this paper, we propose...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7943714/ https://www.ncbi.nlm.nih.gov/pubmed/33719356 http://dx.doi.org/10.1186/s13662-021-03272-5 |
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author | Pan, Weiqiu Li, Tianzeng Ali, Safdar |
author_facet | Pan, Weiqiu Li, Tianzeng Ali, Safdar |
author_sort | Pan, Weiqiu |
collection | PubMed |
description | The Ebola outbreak in 2014 caused many infections and deaths. Some literature works have proposed some models to study Ebola virus, such as SIR, SIS, SEIR, etc. It is proved that the fractional order model can describe epidemic dynamics better than the integer order model. In this paper, we propose a fractional order Ebola system and analyze the nonnegative solution, the basic reproduction number [Formula: see text] , and the stabilities of equilibrium points for the system firstly. In many studies, the numerical solutions of some models cannot fit very well with the real data. Thus, to show the dynamics of the Ebola epidemic, the Gorenflo–Mainardi–Moretti–Paradisi scheme (GMMP) is taken to get the numerical solution of the SEIR fractional order Ebola system and the modified grid approximation method (MGAM) is used to acquire the parameters of the SEIR fractional order Ebola system. We consider that the GMMP method may lead to absurd numerical solutions, so its stability and convergence are given. Then, the new fractional orders, parameters, and the root-mean-square relative error [Formula: see text] are obtained. With the new fractional orders and parameters, the numerical solution of the SEIR fractional order Ebola system is closer to the real data than those models in other literature works. Meanwhile, we find that most of the fractional order Ebola systems have the same order. Hence, the fractional order Ebola system with different orders using the Caputo derivatives is also studied. We also adopt the MGAM algorithm to obtain the new orders, parameters, and the root-mean-square relative error which is [Formula: see text] . With the new parameters and orders, the fractional order Ebola systems with different orders fit very well with the real data. |
format | Online Article Text |
id | pubmed-7943714 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-79437142021-03-10 A fractional order epidemic model for the simulation of outbreaks of Ebola Pan, Weiqiu Li, Tianzeng Ali, Safdar Adv Differ Equ Research The Ebola outbreak in 2014 caused many infections and deaths. Some literature works have proposed some models to study Ebola virus, such as SIR, SIS, SEIR, etc. It is proved that the fractional order model can describe epidemic dynamics better than the integer order model. In this paper, we propose a fractional order Ebola system and analyze the nonnegative solution, the basic reproduction number [Formula: see text] , and the stabilities of equilibrium points for the system firstly. In many studies, the numerical solutions of some models cannot fit very well with the real data. Thus, to show the dynamics of the Ebola epidemic, the Gorenflo–Mainardi–Moretti–Paradisi scheme (GMMP) is taken to get the numerical solution of the SEIR fractional order Ebola system and the modified grid approximation method (MGAM) is used to acquire the parameters of the SEIR fractional order Ebola system. We consider that the GMMP method may lead to absurd numerical solutions, so its stability and convergence are given. Then, the new fractional orders, parameters, and the root-mean-square relative error [Formula: see text] are obtained. With the new fractional orders and parameters, the numerical solution of the SEIR fractional order Ebola system is closer to the real data than those models in other literature works. Meanwhile, we find that most of the fractional order Ebola systems have the same order. Hence, the fractional order Ebola system with different orders using the Caputo derivatives is also studied. We also adopt the MGAM algorithm to obtain the new orders, parameters, and the root-mean-square relative error which is [Formula: see text] . With the new parameters and orders, the fractional order Ebola systems with different orders fit very well with the real data. Springer International Publishing 2021-03-10 2021 /pmc/articles/PMC7943714/ /pubmed/33719356 http://dx.doi.org/10.1186/s13662-021-03272-5 Text en © The Author(s) 2021 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 | Research Pan, Weiqiu Li, Tianzeng Ali, Safdar A fractional order epidemic model for the simulation of outbreaks of Ebola |
title | A fractional order epidemic model for the simulation of outbreaks of Ebola |
title_full | A fractional order epidemic model for the simulation of outbreaks of Ebola |
title_fullStr | A fractional order epidemic model for the simulation of outbreaks of Ebola |
title_full_unstemmed | A fractional order epidemic model for the simulation of outbreaks of Ebola |
title_short | A fractional order epidemic model for the simulation of outbreaks of Ebola |
title_sort | fractional order epidemic model for the simulation of outbreaks of ebola |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7943714/ https://www.ncbi.nlm.nih.gov/pubmed/33719356 http://dx.doi.org/10.1186/s13662-021-03272-5 |
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