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Analytical features of the SIR model and their applications to COVID-19

A classic two-parameter epidemiological SIR-model of the coronavirus propagation is considered. The first integrals of the system of non-linear equations are obtained. The Painlevé test shows that the system of equations is not integrable in the general case. However, the general solution is obtaine...

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Autores principales: Kudryashov, Nikolay A., Chmykhov, Mikhail A., Vigdorowitsch, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7521893/
https://www.ncbi.nlm.nih.gov/pubmed/33012957
http://dx.doi.org/10.1016/j.apm.2020.08.057
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author Kudryashov, Nikolay A.
Chmykhov, Mikhail A.
Vigdorowitsch, Michael
author_facet Kudryashov, Nikolay A.
Chmykhov, Mikhail A.
Vigdorowitsch, Michael
author_sort Kudryashov, Nikolay A.
collection PubMed
description A classic two-parameter epidemiological SIR-model of the coronavirus propagation is considered. The first integrals of the system of non-linear equations are obtained. The Painlevé test shows that the system of equations is not integrable in the general case. However, the general solution is obtained in quadrature as an inverse time-function. Using the first integrals of the system of equations, analytical dependencies for the number of infected patients I(t) and that of recovered patients R(t) on the number of susceptible to infection S(t) are obtained. A particular attention is paid to interrelation of I(t) and R(t) both depending on α/β, where α is the contact rate in the community and β is the intensity of recovery/decease of patients. It is demonstrated that the data on particular morbidity waves in Hubei (China), Italy, Austria, South Korea, Moscow (Russia) as well some Australian territories are satisfactorily described by the expressions obtained for I(R). The variability of parameter N having been traditionally considered as a static population size is discussed.
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spelling pubmed-75218932020-09-29 Analytical features of the SIR model and their applications to COVID-19 Kudryashov, Nikolay A. Chmykhov, Mikhail A. Vigdorowitsch, Michael Appl Math Model Article A classic two-parameter epidemiological SIR-model of the coronavirus propagation is considered. The first integrals of the system of non-linear equations are obtained. The Painlevé test shows that the system of equations is not integrable in the general case. However, the general solution is obtained in quadrature as an inverse time-function. Using the first integrals of the system of equations, analytical dependencies for the number of infected patients I(t) and that of recovered patients R(t) on the number of susceptible to infection S(t) are obtained. A particular attention is paid to interrelation of I(t) and R(t) both depending on α/β, where α is the contact rate in the community and β is the intensity of recovery/decease of patients. It is demonstrated that the data on particular morbidity waves in Hubei (China), Italy, Austria, South Korea, Moscow (Russia) as well some Australian territories are satisfactorily described by the expressions obtained for I(R). The variability of parameter N having been traditionally considered as a static population size is discussed. Elsevier Inc. 2021-02 2020-09-28 /pmc/articles/PMC7521893/ /pubmed/33012957 http://dx.doi.org/10.1016/j.apm.2020.08.057 Text en © 2020 Elsevier Inc. 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
Kudryashov, Nikolay A.
Chmykhov, Mikhail A.
Vigdorowitsch, Michael
Analytical features of the SIR model and their applications to COVID-19
title Analytical features of the SIR model and their applications to COVID-19
title_full Analytical features of the SIR model and their applications to COVID-19
title_fullStr Analytical features of the SIR model and their applications to COVID-19
title_full_unstemmed Analytical features of the SIR model and their applications to COVID-19
title_short Analytical features of the SIR model and their applications to COVID-19
title_sort analytical features of the sir model and their applications to covid-19
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7521893/
https://www.ncbi.nlm.nih.gov/pubmed/33012957
http://dx.doi.org/10.1016/j.apm.2020.08.057
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