A modified SEIR model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks

Abstract COVID-19 is a highly infectious disease that emerged in China at the end of 2019. The COVID-19 pandemic is the first known pandemic caused by a coronavirus, namely, the new and emerging SARS-CoV-2 coronavirus. In the present work, we present simulations of the initial outbreak of this new c...

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Autores principales:	Wilfredo Angulo, José M. Ramírez, Dany De Cecchis, Juan Primera, Henry Pacheco, Eduardo Rodríguez-Román
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/bc9a6485e1904e17b6e178a8f52f5122
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spelling	oai:doaj.org-article:bc9a6485e1904e17b6e178a8f52f51222021-12-02T15:08:23ZA modified SEIR model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks10.1038/s41598-021-95785-y2045-2322https://doaj.org/article/bc9a6485e1904e17b6e178a8f52f51222021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-95785-yhttps://doaj.org/toc/2045-2322Abstract COVID-19 is a highly infectious disease that emerged in China at the end of 2019. The COVID-19 pandemic is the first known pandemic caused by a coronavirus, namely, the new and emerging SARS-CoV-2 coronavirus. In the present work, we present simulations of the initial outbreak of this new coronavirus using a modified transmission rate SEIR model that takes into account the impact of government actions and the perception of risk by individuals in reaction to the proportion of fatal cases. The parameters related to these effects were fitted to the number of infected cases in the 33 provinces of China. The data for Hubei Province, the probable site of origin of the current pandemic, were considered as a particular case for the simulation and showed that the theoretical model reproduces the behavior of the data, thus indicating the importance of combining government actions and individual risk perceptions when the proportion of fatal cases is greater than $$4\%$$ 4 % . The results show that the adjusted model reproduces the behavior of the data quite well for some provinces, suggesting that the spread of the disease differs when different actions are evaluated. The proposed model could help to predict outbreaks of viruses with a biological and molecular structure similar to that of SARS-CoV-2.Wilfredo AnguloJosé M. RamírezDany De CecchisJuan PrimeraHenry PachecoEduardo Rodríguez-RománNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Wilfredo Angulo José M. Ramírez Dany De Cecchis Juan Primera Henry Pacheco Eduardo Rodríguez-Román A modified SEIR model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks
description	Abstract COVID-19 is a highly infectious disease that emerged in China at the end of 2019. The COVID-19 pandemic is the first known pandemic caused by a coronavirus, namely, the new and emerging SARS-CoV-2 coronavirus. In the present work, we present simulations of the initial outbreak of this new coronavirus using a modified transmission rate SEIR model that takes into account the impact of government actions and the perception of risk by individuals in reaction to the proportion of fatal cases. The parameters related to these effects were fitted to the number of infected cases in the 33 provinces of China. The data for Hubei Province, the probable site of origin of the current pandemic, were considered as a particular case for the simulation and showed that the theoretical model reproduces the behavior of the data, thus indicating the importance of combining government actions and individual risk perceptions when the proportion of fatal cases is greater than $$4\%$$ 4 % . The results show that the adjusted model reproduces the behavior of the data quite well for some provinces, suggesting that the spread of the disease differs when different actions are evaluated. The proposed model could help to predict outbreaks of viruses with a biological and molecular structure similar to that of SARS-CoV-2.
format	article
author	Wilfredo Angulo José M. Ramírez Dany De Cecchis Juan Primera Henry Pacheco Eduardo Rodríguez-Román
author_facet	Wilfredo Angulo José M. Ramírez Dany De Cecchis Juan Primera Henry Pacheco Eduardo Rodríguez-Román
author_sort	Wilfredo Angulo
title	A modified SEIR model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks
title_short	A modified SEIR model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks
title_full	A modified SEIR model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks
title_fullStr	A modified SEIR model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks
title_full_unstemmed	A modified SEIR model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks
title_sort	modified seir model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/bc9a6485e1904e17b6e178a8f52f5122
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A modified SEIR model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks

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