A Markov chain model to investigate the spread of antibiotic-resistant bacteria in hospitals

Detalhes bibliográficos
Autor(a) principal: Chalub, Fabio A. C. C.
Data de Publicação: 2023
Outros Autores: Gómez-Corral, Antonio, López-García, Martín, Palacios-Rodríguez, Fátima
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/164080
Resumo: Funding Information: This research was supported by the Government of Spain (Ministry of Science and Innovation), project PGC2018‐097704‐B‐I00. FACCC was partially funded by Fundação para a Ciência e a Tecnologia (Portugal), projects UID/MAT/00297/2019, UIDB/00297/2020, UIDP/00297/2020, and 2022.03091.PTDC. Publisher Copyright: © 2023 The Authors. Studies in Applied Mathematics published by Wiley Periodicals LLC.
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spelling A Markov chain model to investigate the spread of antibiotic-resistant bacteria in hospitalsepidemic modelMarkov chainquasi-birth-death processreproduction numberApplied MathematicsSDG 3 - Good Health and Well-beingFunding Information: This research was supported by the Government of Spain (Ministry of Science and Innovation), project PGC2018‐097704‐B‐I00. FACCC was partially funded by Fundação para a Ciência e a Tecnologia (Portugal), projects UID/MAT/00297/2019, UIDB/00297/2020, UIDP/00297/2020, and 2022.03091.PTDC. Publisher Copyright: © 2023 The Authors. Studies in Applied Mathematics published by Wiley Periodicals LLC.Ordinary differential equation models used in mathematical epidemiology assume explicitly or implicitly large populations. For the study of infections in a hospital, this is an extremely restrictive assumption as typically a hospital ward has a few dozen, or even fewer, patients. This work reframes a well-known model used in the study of the spread of antibiotic-resistant bacteria in hospitals, to consider the pathogen transmission dynamics in small populations. In this vein, this paper proposes a Markov chain model to describe the spread of a single bacterial species in a hospital ward where patients may be free of bacteria or may carry bacterial strains that are either sensitive or resistant to antimicrobial agents. We determine the probability law of the exact reproduction number (Formula presented.), which is here defined as the random number of secondary infections generated by those patients who are accommodated in a predetermined bed before a patient who is free of bacteria is accommodated in this bed for the first time. Specifically, we decompose the exact reproduction number (Formula presented.) into two contributions allowing us to distinguish between infections due to the sensitive and the resistant bacterial strains. Our methodology is mainly based on structured Markov chains and the use of related matrix-analytic methods. This guarantees the compatibility of the new, finite-population model, with large population models present in the literature and takes full advantage, in its mathematical analysis, of the intrinsic stochasticity.CMA - Centro de Matemática e AplicaçõesDM - Departamento de MatemáticaRUNChalub, Fabio A. C. C.Gómez-Corral, AntonioLópez-García, MartínPalacios-Rodríguez, Fátima2024-02-24T00:05:11Z2023-112023-11-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article27application/pdfhttp://hdl.handle.net/10362/164080eng0022-2526PURE: 83891021https://doi.org/10.1111/sapm.12637info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:50:42Zoai:run.unl.pt:10362/164080Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T04:00:02.324043Repositório 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 A Markov chain model to investigate the spread of antibiotic-resistant bacteria in hospitals
title A Markov chain model to investigate the spread of antibiotic-resistant bacteria in hospitals
spellingShingle A Markov chain model to investigate the spread of antibiotic-resistant bacteria in hospitals
Chalub, Fabio A. C. C.
epidemic model
Markov chain
quasi-birth-death process
reproduction number
Applied Mathematics
SDG 3 - Good Health and Well-being
title_short A Markov chain model to investigate the spread of antibiotic-resistant bacteria in hospitals
title_full A Markov chain model to investigate the spread of antibiotic-resistant bacteria in hospitals
title_fullStr A Markov chain model to investigate the spread of antibiotic-resistant bacteria in hospitals
title_full_unstemmed A Markov chain model to investigate the spread of antibiotic-resistant bacteria in hospitals
title_sort A Markov chain model to investigate the spread of antibiotic-resistant bacteria in hospitals
author Chalub, Fabio A. C. C.
author_facet Chalub, Fabio A. C. C.
Gómez-Corral, Antonio
López-García, Martín
Palacios-Rodríguez, Fátima
author_role author
author2 Gómez-Corral, Antonio
López-García, Martín
Palacios-Rodríguez, Fátima
author2_role author
author
author
dc.contributor.none.fl_str_mv CMA - Centro de Matemática e Aplicações
DM - Departamento de Matemática
RUN
dc.contributor.author.fl_str_mv Chalub, Fabio A. C. C.
Gómez-Corral, Antonio
López-García, Martín
Palacios-Rodríguez, Fátima
dc.subject.por.fl_str_mv epidemic model
Markov chain
quasi-birth-death process
reproduction number
Applied Mathematics
SDG 3 - Good Health and Well-being
topic epidemic model
Markov chain
quasi-birth-death process
reproduction number
Applied Mathematics
SDG 3 - Good Health and Well-being
description Funding Information: This research was supported by the Government of Spain (Ministry of Science and Innovation), project PGC2018‐097704‐B‐I00. FACCC was partially funded by Fundação para a Ciência e a Tecnologia (Portugal), projects UID/MAT/00297/2019, UIDB/00297/2020, UIDP/00297/2020, and 2022.03091.PTDC. Publisher Copyright: © 2023 The Authors. Studies in Applied Mathematics published by Wiley Periodicals LLC.
publishDate 2023
dc.date.none.fl_str_mv 2023-11
2023-11-01T00:00:00Z
2024-02-24T00:05:11Z
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/10362/164080
url http://hdl.handle.net/10362/164080
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0022-2526
PURE: 83891021
https://doi.org/10.1111/sapm.12637
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 27
application/pdf
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
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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
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