Unveiling time in dose-response models to infer host susceptibility to pathogens

Detalhes bibliográficos
Autor(a) principal: Pessoa, Delphine
Data de Publicação: 2014
Outros Autores: Souto-Maior, Caetano, Gjini, Erida, Lopes, Joao S, Ceña, Bruno, Codeço, Cláudia T, Gomes, M Gabriela M
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.7/346
Resumo: The biological effects of interventions to control infectious diseases typically depend on the intensity of pathogen challenge. As much as the levels of natural pathogen circulation vary over time and geographical location, the development of invariant efficacy measures is of major importance, even if only indirectly inferrable. Here a method is introduced to assess host susceptibility to pathogens, and applied to a detailed dataset generated by challenging groups of insect hosts (Drosophila melanogaster) with a range of pathogen (Drosophila C Virus) doses and recording survival over time. The experiment was replicated for flies carrying the Wolbachia symbiont, which is known to reduce host susceptibility to viral infections. The entire dataset is fitted by a novel quantitative framework that significantly extends classical methods for microbial risk assessment and provides accurate distributions of symbiont-induced protection. More generally, our data-driven modeling procedure provides novel insights for study design and analyses to assess interventions.
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spelling Unveiling time in dose-response models to infer host susceptibility to pathogensPathogensThe biological effects of interventions to control infectious diseases typically depend on the intensity of pathogen challenge. As much as the levels of natural pathogen circulation vary over time and geographical location, the development of invariant efficacy measures is of major importance, even if only indirectly inferrable. Here a method is introduced to assess host susceptibility to pathogens, and applied to a detailed dataset generated by challenging groups of insect hosts (Drosophila melanogaster) with a range of pathogen (Drosophila C Virus) doses and recording survival over time. The experiment was replicated for flies carrying the Wolbachia symbiont, which is known to reduce host susceptibility to viral infections. The entire dataset is fitted by a novel quantitative framework that significantly extends classical methods for microbial risk assessment and provides accurate distributions of symbiont-induced protection. More generally, our data-driven modeling procedure provides novel insights for study design and analyses to assess interventions.Fundação para a Ciência e Tecnologia.PLOSARCAPessoa, DelphineSouto-Maior, CaetanoGjini, EridaLopes, Joao SCeña, BrunoCodeço, Cláudia TGomes, M Gabriela M2015-10-05T11:08:50Z2014-08-142014-08-14T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.7/346engPessoa D, Souto-Maior C, Gjini E, Lopes JS, Cen ̃ a B, et al. (2014) Unveiling Time in Dose-Response Models to Infer Host Susceptibility to Pathogens. PLoS Comput Biol 10(8): e1003773. doi:10.1371/journal.pcbi.100377310.1371/journal.pcbi.1003773info: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:RCAAP2022-11-29T14:34:44Zoai:arca.igc.gulbenkian.pt:10400.7/346Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:11:39.510101Repositório 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 Unveiling time in dose-response models to infer host susceptibility to pathogens
title Unveiling time in dose-response models to infer host susceptibility to pathogens
spellingShingle Unveiling time in dose-response models to infer host susceptibility to pathogens
Pessoa, Delphine
Pathogens
title_short Unveiling time in dose-response models to infer host susceptibility to pathogens
title_full Unveiling time in dose-response models to infer host susceptibility to pathogens
title_fullStr Unveiling time in dose-response models to infer host susceptibility to pathogens
title_full_unstemmed Unveiling time in dose-response models to infer host susceptibility to pathogens
title_sort Unveiling time in dose-response models to infer host susceptibility to pathogens
author Pessoa, Delphine
author_facet Pessoa, Delphine
Souto-Maior, Caetano
Gjini, Erida
Lopes, Joao S
Ceña, Bruno
Codeço, Cláudia T
Gomes, M Gabriela M
author_role author
author2 Souto-Maior, Caetano
Gjini, Erida
Lopes, Joao S
Ceña, Bruno
Codeço, Cláudia T
Gomes, M Gabriela M
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv ARCA
dc.contributor.author.fl_str_mv Pessoa, Delphine
Souto-Maior, Caetano
Gjini, Erida
Lopes, Joao S
Ceña, Bruno
Codeço, Cláudia T
Gomes, M Gabriela M
dc.subject.por.fl_str_mv Pathogens
topic Pathogens
description The biological effects of interventions to control infectious diseases typically depend on the intensity of pathogen challenge. As much as the levels of natural pathogen circulation vary over time and geographical location, the development of invariant efficacy measures is of major importance, even if only indirectly inferrable. Here a method is introduced to assess host susceptibility to pathogens, and applied to a detailed dataset generated by challenging groups of insect hosts (Drosophila melanogaster) with a range of pathogen (Drosophila C Virus) doses and recording survival over time. The experiment was replicated for flies carrying the Wolbachia symbiont, which is known to reduce host susceptibility to viral infections. The entire dataset is fitted by a novel quantitative framework that significantly extends classical methods for microbial risk assessment and provides accurate distributions of symbiont-induced protection. More generally, our data-driven modeling procedure provides novel insights for study design and analyses to assess interventions.
publishDate 2014
dc.date.none.fl_str_mv 2014-08-14
2014-08-14T00:00:00Z
2015-10-05T11:08:50Z
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/10400.7/346
url http://hdl.handle.net/10400.7/346
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Pessoa D, Souto-Maior C, Gjini E, Lopes JS, Cen ̃ a B, et al. (2014) Unveiling Time in Dose-Response Models to Infer Host Susceptibility to Pathogens. PLoS Comput Biol 10(8): e1003773. doi:10.1371/journal.pcbi.1003773
10.1371/journal.pcbi.1003773
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dc.publisher.none.fl_str_mv PLOS
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