Complex network model for COVID-19: human behavior, pseudo-periodic solutions and multiple epidemic waves
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10773/34444 |
Resumo: | We propose a mathematical model for the transmission dynamics of SARS-CoV-2 in a homogeneously mixing non constant population, and generalize it to a model where the parameters are given by piecewise constant functions. This allows us to model the human behavior and the impact of public health policies on the dynamics of the curve of active infected individuals during a COVID-19 epidemic outbreak. After proving the existence and global asymptotic stability of the disease-free and endemic equilibrium points of the model with constant parameters, we consider a family of Cauchy problems, with piecewise constant parameters, and prove the existence of pseudo-oscillations between a neighborhood of the disease-free equilibrium and a neighborhood of the endemic equilibrium, in a biologically feasible region. In the context of the COVID-19 pandemic, this pseudo-periodic solutions are related to the emergence of epidemic waves. Then, to capture the impact of mobility in the dynamics of COVID-19 epidemics, we propose a complex network with six distinct regions based on COVID-19 real data from Portugal. We perform numerical simulations for the complex network model, where the objective is to determine a topology that minimizes the level of active infected individuals and the existence of topologies that are likely to worsen the level of infection. We claim that this methodology is a tool with enormous potential in the current pandemic context, and can be applied in the management of outbreaks (in regional terms) but also to manage the opening/closing of borders. |
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Complex network model for COVID-19: human behavior, pseudo-periodic solutions and multiple epidemic wavesCOVID-19 epidemic wavesPiecewise constant parametersPseudo-periodic solutionsComplex networkPortugal case studyWe propose a mathematical model for the transmission dynamics of SARS-CoV-2 in a homogeneously mixing non constant population, and generalize it to a model where the parameters are given by piecewise constant functions. This allows us to model the human behavior and the impact of public health policies on the dynamics of the curve of active infected individuals during a COVID-19 epidemic outbreak. After proving the existence and global asymptotic stability of the disease-free and endemic equilibrium points of the model with constant parameters, we consider a family of Cauchy problems, with piecewise constant parameters, and prove the existence of pseudo-oscillations between a neighborhood of the disease-free equilibrium and a neighborhood of the endemic equilibrium, in a biologically feasible region. In the context of the COVID-19 pandemic, this pseudo-periodic solutions are related to the emergence of epidemic waves. Then, to capture the impact of mobility in the dynamics of COVID-19 epidemics, we propose a complex network with six distinct regions based on COVID-19 real data from Portugal. We perform numerical simulations for the complex network model, where the objective is to determine a topology that minimizes the level of active infected individuals and the existence of topologies that are likely to worsen the level of infection. We claim that this methodology is a tool with enormous potential in the current pandemic context, and can be applied in the management of outbreaks (in regional terms) but also to manage the opening/closing of borders.Elsevier2024-10-15T00:00:00Z2022-10-15T00:00:00Z2022-10-15info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/pdfhttp://hdl.handle.net/10773/34444eng0022-247X10.1016/j.jmaa.2021.125171Silva, Cristiana J.Cantin, GuillaumeCruz, CarlaFonseca-Pinto, RuiPassadouro, RuiSantos, Estevão Soares dosTorres, Delfim F. M.info:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T12:05:35Zoai:ria.ua.pt:10773/34444Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:05:24.263330Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Complex network model for COVID-19: human behavior, pseudo-periodic solutions and multiple epidemic waves |
title |
Complex network model for COVID-19: human behavior, pseudo-periodic solutions and multiple epidemic waves |
spellingShingle |
Complex network model for COVID-19: human behavior, pseudo-periodic solutions and multiple epidemic waves Silva, Cristiana J. COVID-19 epidemic waves Piecewise constant parameters Pseudo-periodic solutions Complex network Portugal case study |
title_short |
Complex network model for COVID-19: human behavior, pseudo-periodic solutions and multiple epidemic waves |
title_full |
Complex network model for COVID-19: human behavior, pseudo-periodic solutions and multiple epidemic waves |
title_fullStr |
Complex network model for COVID-19: human behavior, pseudo-periodic solutions and multiple epidemic waves |
title_full_unstemmed |
Complex network model for COVID-19: human behavior, pseudo-periodic solutions and multiple epidemic waves |
title_sort |
Complex network model for COVID-19: human behavior, pseudo-periodic solutions and multiple epidemic waves |
author |
Silva, Cristiana J. |
author_facet |
Silva, Cristiana J. Cantin, Guillaume Cruz, Carla Fonseca-Pinto, Rui Passadouro, Rui Santos, Estevão Soares dos Torres, Delfim F. M. |
author_role |
author |
author2 |
Cantin, Guillaume Cruz, Carla Fonseca-Pinto, Rui Passadouro, Rui Santos, Estevão Soares dos Torres, Delfim F. M. |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Silva, Cristiana J. Cantin, Guillaume Cruz, Carla Fonseca-Pinto, Rui Passadouro, Rui Santos, Estevão Soares dos Torres, Delfim F. M. |
dc.subject.por.fl_str_mv |
COVID-19 epidemic waves Piecewise constant parameters Pseudo-periodic solutions Complex network Portugal case study |
topic |
COVID-19 epidemic waves Piecewise constant parameters Pseudo-periodic solutions Complex network Portugal case study |
description |
We propose a mathematical model for the transmission dynamics of SARS-CoV-2 in a homogeneously mixing non constant population, and generalize it to a model where the parameters are given by piecewise constant functions. This allows us to model the human behavior and the impact of public health policies on the dynamics of the curve of active infected individuals during a COVID-19 epidemic outbreak. After proving the existence and global asymptotic stability of the disease-free and endemic equilibrium points of the model with constant parameters, we consider a family of Cauchy problems, with piecewise constant parameters, and prove the existence of pseudo-oscillations between a neighborhood of the disease-free equilibrium and a neighborhood of the endemic equilibrium, in a biologically feasible region. In the context of the COVID-19 pandemic, this pseudo-periodic solutions are related to the emergence of epidemic waves. Then, to capture the impact of mobility in the dynamics of COVID-19 epidemics, we propose a complex network with six distinct regions based on COVID-19 real data from Portugal. We perform numerical simulations for the complex network model, where the objective is to determine a topology that minimizes the level of active infected individuals and the existence of topologies that are likely to worsen the level of infection. We claim that this methodology is a tool with enormous potential in the current pandemic context, and can be applied in the management of outbreaks (in regional terms) but also to manage the opening/closing of borders. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-10-15T00:00:00Z 2022-10-15 2024-10-15T00:00:00Z |
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://hdl.handle.net/10773/34444 |
url |
http://hdl.handle.net/10773/34444 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0022-247X 10.1016/j.jmaa.2021.125171 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799137708784746496 |