A Bayesian stochastic SIRS model with a vaccination strategy for the analysis of respiratory syncytial virus

Our objective in this paper is to model the dynamics of respiratory syncytial virus in the region of Valencia (Spain) and analyse the effect of vaccination strategies from a health-economic point of view. Compartmental mathematical models based on differential equations are commonly used in epidemio...

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Detalhes bibliográficos
Autores: Jornet-Sanz, Marc, Corberán-Vallet, Ana, Santonja, Francisco, Villanueva, Rafael
Formato: artículo
Fecha de publicación:2017
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/112757
Acesso em linha:https://hdl.handle.net/2117/112757
Access Level:acceso abierto
Palavra-chave:Infectious diseases
respiratory syncytial virus (RSV)
discrete-time epidemic model
stochastic compartmental model
Bayesian analysis
intervention strategies
Classificació AMS::62 Statistics::62P Applications
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
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network_acronym_str ES
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repository_id_str
spelling A Bayesian stochastic SIRS model with a vaccination strategy for the analysis of respiratory syncytial virusJornet-Sanz, MarcCorberán-Vallet, AnaSantonja, FranciscoVillanueva, RafaelInfectious diseasesrespiratory syncytial virus (RSV)discrete-time epidemic modelstochastic compartmental modelBayesian analysisintervention strategiesClassificació AMS::62 Statistics::62P ApplicationsÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàticaOur objective in this paper is to model the dynamics of respiratory syncytial virus in the region of Valencia (Spain) and analyse the effect of vaccination strategies from a health-economic point of view. Compartmental mathematical models based on differential equations are commonly used in epidemiology to both understand the underlying mechanisms that influence disease transmission and analyse the impact of vaccination programs. However, a recently proposed Bayesian stochastic susceptible-infected-recovered-susceptible model in discrete-time provided an improved and more natural description of disease dynamics. In this work, we propose an extension of that stochastic model that allows us to simulate and assess the effect of a vaccination strategy that consists on vaccinating a proportion of newborns.Peer ReviewedInstitut d'Estadística de Catalunya20172017-06-2120182018-01-12journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/112757reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1127572026-05-27T15:37:01Z
dc.title.none.fl_str_mv A Bayesian stochastic SIRS model with a vaccination strategy for the analysis of respiratory syncytial virus
title A Bayesian stochastic SIRS model with a vaccination strategy for the analysis of respiratory syncytial virus
spellingShingle A Bayesian stochastic SIRS model with a vaccination strategy for the analysis of respiratory syncytial virus
Jornet-Sanz, Marc
Infectious diseases
respiratory syncytial virus (RSV)
discrete-time epidemic model
stochastic compartmental model
Bayesian analysis
intervention strategies
Classificació AMS::62 Statistics::62P Applications
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
title_short A Bayesian stochastic SIRS model with a vaccination strategy for the analysis of respiratory syncytial virus
title_full A Bayesian stochastic SIRS model with a vaccination strategy for the analysis of respiratory syncytial virus
title_fullStr A Bayesian stochastic SIRS model with a vaccination strategy for the analysis of respiratory syncytial virus
title_full_unstemmed A Bayesian stochastic SIRS model with a vaccination strategy for the analysis of respiratory syncytial virus
title_sort A Bayesian stochastic SIRS model with a vaccination strategy for the analysis of respiratory syncytial virus
dc.creator.none.fl_str_mv Jornet-Sanz, Marc
Corberán-Vallet, Ana
Santonja, Francisco
Villanueva, Rafael
author Jornet-Sanz, Marc
author_facet Jornet-Sanz, Marc
Corberán-Vallet, Ana
Santonja, Francisco
Villanueva, Rafael
author_role author
author2 Corberán-Vallet, Ana
Santonja, Francisco
Villanueva, Rafael
author2_role author
author
author
dc.subject.none.fl_str_mv Infectious diseases
respiratory syncytial virus (RSV)
discrete-time epidemic model
stochastic compartmental model
Bayesian analysis
intervention strategies
Classificació AMS::62 Statistics::62P Applications
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
topic Infectious diseases
respiratory syncytial virus (RSV)
discrete-time epidemic model
stochastic compartmental model
Bayesian analysis
intervention strategies
Classificació AMS::62 Statistics::62P Applications
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
description Our objective in this paper is to model the dynamics of respiratory syncytial virus in the region of Valencia (Spain) and analyse the effect of vaccination strategies from a health-economic point of view. Compartmental mathematical models based on differential equations are commonly used in epidemiology to both understand the underlying mechanisms that influence disease transmission and analyse the impact of vaccination programs. However, a recently proposed Bayesian stochastic susceptible-infected-recovered-susceptible model in discrete-time provided an improved and more natural description of disease dynamics. In this work, we propose an extension of that stochastic model that allows us to simulate and assess the effect of a vaccination strategy that consists on vaccinating a proportion of newborns.
publishDate 2017
dc.date.none.fl_str_mv 2017
2017-06-21
2018
2018-01-12
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/112757
url https://hdl.handle.net/2117/112757
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Institut d'Estadística de Catalunya
publisher.none.fl_str_mv Institut d'Estadística de Catalunya
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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