Numerical study of SARS epidemic model with the inclusion of diffusion in the system

This paper deals with the numerical study of population model based on the epidemics of Severe Acute Respiratory Syndrome (SARS). SEIJR (susceptible, exposed, infected, diagnosed, recovered) model of SARS epidemic is considered with net in flow of individuals into a region. Transmission of disease i...

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Detalles Bibliográficos
Autores principales: Naheed, Afia, Singh, Manmohan, Lucy, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published by Elsevier Inc. 2014
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112316/
https://www.ncbi.nlm.nih.gov/pubmed/32287498
http://dx.doi.org/10.1016/j.amc.2013.12.062
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author Naheed, Afia
Singh, Manmohan
Lucy, David
author_facet Naheed, Afia
Singh, Manmohan
Lucy, David
author_sort Naheed, Afia
collection PubMed
description This paper deals with the numerical study of population model based on the epidemics of Severe Acute Respiratory Syndrome (SARS). SEIJR (susceptible, exposed, infected, diagnosed, recovered) model of SARS epidemic is considered with net in flow of individuals into a region. Transmission of disease is analyzed by solving the system of differential equations using numerical methods with different initial population distributions. The effect of diffusion on the spread of disease is examined. Stability is established for the numerical solutions. Effects of interventions (medical and non medical) are also analyzed.
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spelling pubmed-71123162020-04-02 Numerical study of SARS epidemic model with the inclusion of diffusion in the system Naheed, Afia Singh, Manmohan Lucy, David Appl Math Comput Article This paper deals with the numerical study of population model based on the epidemics of Severe Acute Respiratory Syndrome (SARS). SEIJR (susceptible, exposed, infected, diagnosed, recovered) model of SARS epidemic is considered with net in flow of individuals into a region. Transmission of disease is analyzed by solving the system of differential equations using numerical methods with different initial population distributions. The effect of diffusion on the spread of disease is examined. Stability is established for the numerical solutions. Effects of interventions (medical and non medical) are also analyzed. Published by Elsevier Inc. 2014-02-25 2014-01-17 /pmc/articles/PMC7112316/ /pubmed/32287498 http://dx.doi.org/10.1016/j.amc.2013.12.062 Text en Crown copyright © 2013 Published by 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
Naheed, Afia
Singh, Manmohan
Lucy, David
Numerical study of SARS epidemic model with the inclusion of diffusion in the system
title Numerical study of SARS epidemic model with the inclusion of diffusion in the system
title_full Numerical study of SARS epidemic model with the inclusion of diffusion in the system
title_fullStr Numerical study of SARS epidemic model with the inclusion of diffusion in the system
title_full_unstemmed Numerical study of SARS epidemic model with the inclusion of diffusion in the system
title_short Numerical study of SARS epidemic model with the inclusion of diffusion in the system
title_sort numerical study of sars epidemic model with the inclusion of diffusion in the system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112316/
https://www.ncbi.nlm.nih.gov/pubmed/32287498
http://dx.doi.org/10.1016/j.amc.2013.12.062
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