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Mathematical computations on epidemiology: a case study of the novel coronavirus (SARS-CoV-2)

The outbreak of coronavirus COVID-19 is spreading at an unprecedented rate to the human populations and taking several thousands of life all over the world. Scientists are trying to map the pattern of the transmission of coronavirus (SARS-CoV-2). Many countries are in the phase of lockdown in the gl...

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Autores principales: Batabyal, Saikat, Batabyal, Arthita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7937432/
https://www.ncbi.nlm.nih.gov/pubmed/33682078
http://dx.doi.org/10.1007/s12064-021-00339-5
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author Batabyal, Saikat
Batabyal, Arthita
author_facet Batabyal, Saikat
Batabyal, Arthita
author_sort Batabyal, Saikat
collection PubMed
description The outbreak of coronavirus COVID-19 is spreading at an unprecedented rate to the human populations and taking several thousands of life all over the world. Scientists are trying to map the pattern of the transmission of coronavirus (SARS-CoV-2). Many countries are in the phase of lockdown in the globe. In this paper we predict about the effect of coronavirus COVID-19 and give a sneak peak when it will reduce the transmission rate in the world via mathematical modelling. In this research work our study is based on extensions of the well-known susceptible-exposed-infected-recovered (SEIR) family of compartmental models and later we observe the new model changes into (SEIR) without changing its physical meanings. The stability analysis of the coronavirus depends on changing of its basic reproductive ratio. The progress rate of the virus in the critically infected cases and the recovery rate have major roles to control this epidemic. The impact of social distancing, lockdown of the country, self-isolation, home quarantine and the wariness of global public health system have significant influence on the parameters of the model system that can alter the effect of recovery rates, mortality rates and active contaminated cases with the progression of time in the real world. The prognostic ability of mathematical model is circumscribed as of the accuracy of the available data and its application to the problem.
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spelling pubmed-79374322021-03-08 Mathematical computations on epidemiology: a case study of the novel coronavirus (SARS-CoV-2) Batabyal, Saikat Batabyal, Arthita Theory Biosci Original Article The outbreak of coronavirus COVID-19 is spreading at an unprecedented rate to the human populations and taking several thousands of life all over the world. Scientists are trying to map the pattern of the transmission of coronavirus (SARS-CoV-2). Many countries are in the phase of lockdown in the globe. In this paper we predict about the effect of coronavirus COVID-19 and give a sneak peak when it will reduce the transmission rate in the world via mathematical modelling. In this research work our study is based on extensions of the well-known susceptible-exposed-infected-recovered (SEIR) family of compartmental models and later we observe the new model changes into (SEIR) without changing its physical meanings. The stability analysis of the coronavirus depends on changing of its basic reproductive ratio. The progress rate of the virus in the critically infected cases and the recovery rate have major roles to control this epidemic. The impact of social distancing, lockdown of the country, self-isolation, home quarantine and the wariness of global public health system have significant influence on the parameters of the model system that can alter the effect of recovery rates, mortality rates and active contaminated cases with the progression of time in the real world. The prognostic ability of mathematical model is circumscribed as of the accuracy of the available data and its application to the problem. Springer Berlin Heidelberg 2021-03-07 2021 /pmc/articles/PMC7937432/ /pubmed/33682078 http://dx.doi.org/10.1007/s12064-021-00339-5 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Article
Batabyal, Saikat
Batabyal, Arthita
Mathematical computations on epidemiology: a case study of the novel coronavirus (SARS-CoV-2)
title Mathematical computations on epidemiology: a case study of the novel coronavirus (SARS-CoV-2)
title_full Mathematical computations on epidemiology: a case study of the novel coronavirus (SARS-CoV-2)
title_fullStr Mathematical computations on epidemiology: a case study of the novel coronavirus (SARS-CoV-2)
title_full_unstemmed Mathematical computations on epidemiology: a case study of the novel coronavirus (SARS-CoV-2)
title_short Mathematical computations on epidemiology: a case study of the novel coronavirus (SARS-CoV-2)
title_sort mathematical computations on epidemiology: a case study of the novel coronavirus (sars-cov-2)
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7937432/
https://www.ncbi.nlm.nih.gov/pubmed/33682078
http://dx.doi.org/10.1007/s12064-021-00339-5
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