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Modeling the dynamics of novel coronavirus (2019-nCov) with fractional derivative
The present paper describes the mathematical modeling and dynamics of a novel corona virus (2019-nCoV). We describe the brief details of interaction among the bats and unknown hosts, then among the peoples and the infections reservoir (seafood market). The seafood marked are considered the main sour...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria University.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148705/ http://dx.doi.org/10.1016/j.aej.2020.02.033 |
_version_ | 1783520649689432064 |
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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 | The present paper describes the mathematical modeling and dynamics of a novel corona virus (2019-nCoV). We describe the brief details of interaction among the bats and unknown hosts, then among the peoples and the infections reservoir (seafood market). The seafood marked are considered the main source of infection when the bats and the unknown hosts (may be wild animals) leaves the infection there. The purchasing of items from the seafood market by peoples have the ability to infect either asymptomatically or symptomatically. We reduced the model with the assumptions that the seafood market has enough source of infection that can be effective to infect people. We present the mathematical results of the model and then formulate a fractional model. We consider the available infection cases for January 21, 2020, till January 28, 2020 and parameterized the model. We compute the basic reproduction number for the data is [Formula: see text]. The fractional model is then solved numerically by presenting many graphical results, which can be helpful for the infection minimization. |
format | Online Article Text |
id | pubmed-7148705 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria University. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71487052020-04-13 Modeling the dynamics of novel coronavirus (2019-nCov) with fractional derivative Khan, Muhammad Altaf Atangana, Abdon Alexandria Engineering Journal Original Article The present paper describes the mathematical modeling and dynamics of a novel corona virus (2019-nCoV). We describe the brief details of interaction among the bats and unknown hosts, then among the peoples and the infections reservoir (seafood market). The seafood marked are considered the main source of infection when the bats and the unknown hosts (may be wild animals) leaves the infection there. The purchasing of items from the seafood market by peoples have the ability to infect either asymptomatically or symptomatically. We reduced the model with the assumptions that the seafood market has enough source of infection that can be effective to infect people. We present the mathematical results of the model and then formulate a fractional model. We consider the available infection cases for January 21, 2020, till January 28, 2020 and parameterized the model. We compute the basic reproduction number for the data is [Formula: see text]. The fractional model is then solved numerically by presenting many graphical results, which can be helpful for the infection minimization. The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria University. 2020-08 2020-03-14 /pmc/articles/PMC7148705/ http://dx.doi.org/10.1016/j.aej.2020.02.033 Text en © 2020 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria University. 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 | Original Article Khan, Muhammad Altaf Atangana, Abdon Modeling the dynamics of novel coronavirus (2019-nCov) with fractional derivative |
title | Modeling the dynamics of novel coronavirus (2019-nCov) with fractional derivative |
title_full | Modeling the dynamics of novel coronavirus (2019-nCov) with fractional derivative |
title_fullStr | Modeling the dynamics of novel coronavirus (2019-nCov) with fractional derivative |
title_full_unstemmed | Modeling the dynamics of novel coronavirus (2019-nCov) with fractional derivative |
title_short | Modeling the dynamics of novel coronavirus (2019-nCov) with fractional derivative |
title_sort | modeling the dynamics of novel coronavirus (2019-ncov) with fractional derivative |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148705/ http://dx.doi.org/10.1016/j.aej.2020.02.033 |
work_keys_str_mv | AT khanmuhammadaltaf modelingthedynamicsofnovelcoronavirus2019ncovwithfractionalderivative AT atanganaabdon modelingthedynamicsofnovelcoronavirus2019ncovwithfractionalderivative |