SIRSi compartmental model for COVID-19 pandemic with immunity loss
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.chaos.2020.110388 http://hdl.handle.net/11449/208094 |
Resumo: | The coronavirus disease 2019 (Covid-19) outbreak led the world to an unprecedented health and economic crisis. In an attempt to respond to this emergency, researchers worldwide are intensively studying the dynamics of the Covid-19 pandemic. In this study, a Susceptible - Infected - Removed - Sick (SIRSi) compartmental model is proposed, which is a modification of the classical Susceptible - Infected - Removed (SIR) model. The proposed model considers the possibility of unreported or asymptomatic cases, and differences in the immunity within a population, i.e., the possibility that the acquired immunity may be temporary, which occurs when adopting one of the parameters (γ) other than zero. Local asymptotic stability and endemic equilibrium conditions are proved for the proposed model. The model is adjusted to the data from three major cities of the state of São Paulo in Brazil, namely, São Paulo, Santos, and Campinas, providing estimations of duration and peaks related to the disease propagation. This study reveals that temporary immunity favors a second wave of infection and it depends on the time interval for a recovered person to be susceptible again. It also indicates the possibility that a greater number of patients would get infected with decreased time for reinfection. |
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Repositório Institucional da UNESP |
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SIRSi compartmental model for COVID-19 pandemic with immunity lossCompartmental modelsCovid-19Equilibrium analysisParameter fittingThe coronavirus disease 2019 (Covid-19) outbreak led the world to an unprecedented health and economic crisis. In an attempt to respond to this emergency, researchers worldwide are intensively studying the dynamics of the Covid-19 pandemic. In this study, a Susceptible - Infected - Removed - Sick (SIRSi) compartmental model is proposed, which is a modification of the classical Susceptible - Infected - Removed (SIR) model. The proposed model considers the possibility of unreported or asymptomatic cases, and differences in the immunity within a population, i.e., the possibility that the acquired immunity may be temporary, which occurs when adopting one of the parameters (γ) other than zero. Local asymptotic stability and endemic equilibrium conditions are proved for the proposed model. The model is adjusted to the data from three major cities of the state of São Paulo in Brazil, namely, São Paulo, Santos, and Campinas, providing estimations of duration and peaks related to the disease propagation. This study reveals that temporary immunity favors a second wave of infection and it depends on the time interval for a recovered person to be susceptible again. It also indicates the possibility that a greater number of patients would get infected with decreased time for reinfection.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Polytechnic School of University of São Paulo - EPUSPFederal University of ABC - UFABCSão Paulo State University - UNESPSão Paulo State University - UNESPCNPq: 302883/2018-5Universidade de São Paulo (USP)Universidade Federal do ABC (UFABC)Universidade Estadual Paulista (Unesp)Batistela, Cristiane M.Correa, Diego P.F.Bueno, Átila M [UNESP]Piqueira, José Roberto C.2021-06-25T11:06:12Z2021-06-25T11:06:12Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.chaos.2020.110388Chaos, Solitons and Fractals, v. 142.0960-0779http://hdl.handle.net/11449/20809410.1016/j.chaos.2020.1103882-s2.0-85094857411Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengChaos, Solitons and Fractalsinfo:eu-repo/semantics/openAccess2021-10-23T18:56:33Zoai:repositorio.unesp.br:11449/208094Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T18:56:33Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
SIRSi compartmental model for COVID-19 pandemic with immunity loss |
title |
SIRSi compartmental model for COVID-19 pandemic with immunity loss |
spellingShingle |
SIRSi compartmental model for COVID-19 pandemic with immunity loss Batistela, Cristiane M. Compartmental models Covid-19 Equilibrium analysis Parameter fitting |
title_short |
SIRSi compartmental model for COVID-19 pandemic with immunity loss |
title_full |
SIRSi compartmental model for COVID-19 pandemic with immunity loss |
title_fullStr |
SIRSi compartmental model for COVID-19 pandemic with immunity loss |
title_full_unstemmed |
SIRSi compartmental model for COVID-19 pandemic with immunity loss |
title_sort |
SIRSi compartmental model for COVID-19 pandemic with immunity loss |
author |
Batistela, Cristiane M. |
author_facet |
Batistela, Cristiane M. Correa, Diego P.F. Bueno, Átila M [UNESP] Piqueira, José Roberto C. |
author_role |
author |
author2 |
Correa, Diego P.F. Bueno, Átila M [UNESP] Piqueira, José Roberto C. |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade de São Paulo (USP) Universidade Federal do ABC (UFABC) Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Batistela, Cristiane M. Correa, Diego P.F. Bueno, Átila M [UNESP] Piqueira, José Roberto C. |
dc.subject.por.fl_str_mv |
Compartmental models Covid-19 Equilibrium analysis Parameter fitting |
topic |
Compartmental models Covid-19 Equilibrium analysis Parameter fitting |
description |
The coronavirus disease 2019 (Covid-19) outbreak led the world to an unprecedented health and economic crisis. In an attempt to respond to this emergency, researchers worldwide are intensively studying the dynamics of the Covid-19 pandemic. In this study, a Susceptible - Infected - Removed - Sick (SIRSi) compartmental model is proposed, which is a modification of the classical Susceptible - Infected - Removed (SIR) model. The proposed model considers the possibility of unreported or asymptomatic cases, and differences in the immunity within a population, i.e., the possibility that the acquired immunity may be temporary, which occurs when adopting one of the parameters (γ) other than zero. Local asymptotic stability and endemic equilibrium conditions are proved for the proposed model. The model is adjusted to the data from three major cities of the state of São Paulo in Brazil, namely, São Paulo, Santos, and Campinas, providing estimations of duration and peaks related to the disease propagation. This study reveals that temporary immunity favors a second wave of infection and it depends on the time interval for a recovered person to be susceptible again. It also indicates the possibility that a greater number of patients would get infected with decreased time for reinfection. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06-25T11:06:12Z 2021-06-25T11:06:12Z 2021-01-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/j.chaos.2020.110388 Chaos, Solitons and Fractals, v. 142. 0960-0779 http://hdl.handle.net/11449/208094 10.1016/j.chaos.2020.110388 2-s2.0-85094857411 |
url |
http://dx.doi.org/10.1016/j.chaos.2020.110388 http://hdl.handle.net/11449/208094 |
identifier_str_mv |
Chaos, Solitons and Fractals, v. 142. 0960-0779 10.1016/j.chaos.2020.110388 2-s2.0-85094857411 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Chaos, Solitons and Fractals |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1799965274286325760 |