SIR model with exposure rate for the study of the projection of COVID-19 cases in Sergipe
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | |
Tipo de documento: | preprint |
Idioma: | por |
Título da fonte: | SciELO Preprints |
Texto Completo: | https://preprints.scielo.org/index.php/scielo/preprint/view/311 |
Resumo: | In this work, we used two models to study the behavior of the epidemic curve of COVID-19 in Sergipe between March 14, 2020 and May 2, 2020: conventional SIR model and a variant thereof, which incorporates the number of individuals more exposed to contagion than the rest of the population. We built this variant of the SIR model based on another model proposed to describe the epidemic outbreak of COVID-19 in South Korea and Portugal. In the SIR model with exposure proposed here, we introduced an exposure factor, called β1 / β2, which allows us to describe the influence of factors, such as social withdrawal, on the spread of the disease. In our work, to compare the data obtained through simulation and the number of cases officially registered in Sergipe; we consider that there are between three and nine real cases for each officially registered case, that there are individuals more likely to be infected than others, here exposed individuals, and that the number of reproduction varies over time, growing exponentially in the beginning of the outbreak. epidemic. The simulation results show that the contagion rate is in the range of 2.9 or higher, a region in which there is greater agreement between the model and the data collected. |
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SIR model with exposure rate for the study of the projection of COVID-19 cases in SergipeModelo SIR com taxa de exposição para estudo da projeção de casos de COVID-19 no estado de SergipecoronavírusSARS-CoV-2Modelo SIRSergipecoronavirusSARS-CoV-2SIR modelSergipeIn this work, we used two models to study the behavior of the epidemic curve of COVID-19 in Sergipe between March 14, 2020 and May 2, 2020: conventional SIR model and a variant thereof, which incorporates the number of individuals more exposed to contagion than the rest of the population. We built this variant of the SIR model based on another model proposed to describe the epidemic outbreak of COVID-19 in South Korea and Portugal. In the SIR model with exposure proposed here, we introduced an exposure factor, called β1 / β2, which allows us to describe the influence of factors, such as social withdrawal, on the spread of the disease. In our work, to compare the data obtained through simulation and the number of cases officially registered in Sergipe; we consider that there are between three and nine real cases for each officially registered case, that there are individuals more likely to be infected than others, here exposed individuals, and that the number of reproduction varies over time, growing exponentially in the beginning of the outbreak. epidemic. The simulation results show that the contagion rate is in the range of 2.9 or higher, a region in which there is greater agreement between the model and the data collected.Utilizamos neste trabalho dois modelos para o estudo do comportamento da curva epidêmica da COVID-19 no estado de Sergipe entre os dias 14 de março de 2020 e 02 de maio de 2020: modelo SIR convencional e uma variante deste, que incorpora o número de indivíduos mais expostos ao contágio do que o restante da população. Construímos essa variante do modelo SIR com base em outro modelo proposto para descrever o surto epidêmico da COVID-19 na Coreia do Sul e em Portugal. No modelo SIR com exposição aqui proposto, introduzimos um fator de exposição, denominado β1/β2, que permite descrever a influência de fatores, como afastamento social, no espalhamento da doença. Em nosso trabalho, para fazer a comparação entre os dados obtidos via simulação e o número de casos oficialmente registrados no estado de Sergipe; consideramos que há entre três e nove casos reais para cada caso registrado oficialmente, que há indivíduos com maior probabilidade de contágio do que outros, aqui denominados indivíduos expostos, e que o número de reprodução varia com o tempo, crescendo exponencialmente na fase início do surto epidêmico. Os resultados da simulação mostram que a taxa de contágio se encontra na faixa de 2,9 ou superior, região em que há maior concordância entre o modelo e dados coletados.SciELO PreprintsSciELO PreprintsSciELO Preprints2020-05-06info:eu-repo/semantics/preprintinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://preprints.scielo.org/index.php/scielo/preprint/view/31110.1590/SciELOPreprints.311porhttps://preprints.scielo.org/index.php/scielo/article/view/311/370Copyright (c) 2020 Silvio Sandes, Augusto dos Santos Freitashttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSandes, SilvioFreitas, Augusto dos Santosreponame:SciELO Preprintsinstname:SciELOinstacron:SCI2020-05-03T20:09:38Zoai:ops.preprints.scielo.org:preprint/311Servidor de preprintshttps://preprints.scielo.org/index.php/scieloONGhttps://preprints.scielo.org/index.php/scielo/oaiscielo.submission@scielo.orgopendoar:2020-05-03T20:09:38SciELO Preprints - SciELOfalse |
dc.title.none.fl_str_mv |
SIR model with exposure rate for the study of the projection of COVID-19 cases in Sergipe Modelo SIR com taxa de exposição para estudo da projeção de casos de COVID-19 no estado de Sergipe |
title |
SIR model with exposure rate for the study of the projection of COVID-19 cases in Sergipe |
spellingShingle |
SIR model with exposure rate for the study of the projection of COVID-19 cases in Sergipe Sandes, Silvio coronavírus SARS-CoV-2 Modelo SIR Sergipe coronavirus SARS-CoV-2 SIR model Sergipe |
title_short |
SIR model with exposure rate for the study of the projection of COVID-19 cases in Sergipe |
title_full |
SIR model with exposure rate for the study of the projection of COVID-19 cases in Sergipe |
title_fullStr |
SIR model with exposure rate for the study of the projection of COVID-19 cases in Sergipe |
title_full_unstemmed |
SIR model with exposure rate for the study of the projection of COVID-19 cases in Sergipe |
title_sort |
SIR model with exposure rate for the study of the projection of COVID-19 cases in Sergipe |
author |
Sandes, Silvio |
author_facet |
Sandes, Silvio Freitas, Augusto dos Santos |
author_role |
author |
author2 |
Freitas, Augusto dos Santos |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Sandes, Silvio Freitas, Augusto dos Santos |
dc.subject.por.fl_str_mv |
coronavírus SARS-CoV-2 Modelo SIR Sergipe coronavirus SARS-CoV-2 SIR model Sergipe |
topic |
coronavírus SARS-CoV-2 Modelo SIR Sergipe coronavirus SARS-CoV-2 SIR model Sergipe |
description |
In this work, we used two models to study the behavior of the epidemic curve of COVID-19 in Sergipe between March 14, 2020 and May 2, 2020: conventional SIR model and a variant thereof, which incorporates the number of individuals more exposed to contagion than the rest of the population. We built this variant of the SIR model based on another model proposed to describe the epidemic outbreak of COVID-19 in South Korea and Portugal. In the SIR model with exposure proposed here, we introduced an exposure factor, called β1 / β2, which allows us to describe the influence of factors, such as social withdrawal, on the spread of the disease. In our work, to compare the data obtained through simulation and the number of cases officially registered in Sergipe; we consider that there are between three and nine real cases for each officially registered case, that there are individuals more likely to be infected than others, here exposed individuals, and that the number of reproduction varies over time, growing exponentially in the beginning of the outbreak. epidemic. The simulation results show that the contagion rate is in the range of 2.9 or higher, a region in which there is greater agreement between the model and the data collected. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-05-06 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/preprint info:eu-repo/semantics/publishedVersion |
format |
preprint |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://preprints.scielo.org/index.php/scielo/preprint/view/311 10.1590/SciELOPreprints.311 |
url |
https://preprints.scielo.org/index.php/scielo/preprint/view/311 |
identifier_str_mv |
10.1590/SciELOPreprints.311 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://preprints.scielo.org/index.php/scielo/article/view/311/370 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2020 Silvio Sandes, Augusto dos Santos Freitas https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2020 Silvio Sandes, Augusto dos Santos Freitas https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
SciELO Preprints SciELO Preprints SciELO Preprints |
publisher.none.fl_str_mv |
SciELO Preprints SciELO Preprints SciELO Preprints |
dc.source.none.fl_str_mv |
reponame:SciELO Preprints instname:SciELO instacron:SCI |
instname_str |
SciELO |
instacron_str |
SCI |
institution |
SCI |
reponame_str |
SciELO Preprints |
collection |
SciELO Preprints |
repository.name.fl_str_mv |
SciELO Preprints - SciELO |
repository.mail.fl_str_mv |
scielo.submission@scielo.org |
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1797047817238216704 |