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Sensitivity, uncertainty and identifiability analyses to define a dengue transmission model with real data of an endemic municipality of Colombia

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dc.citation.journalTitlePlos One
dc.contributor.authorLizarralde-Bejarano, D.P.
dc.contributor.authorRojas-Díaz, D.
dc.contributor.authorArboleda-Sánchez, S.
dc.contributor.authorPuerta-Yepes, M.E.
dc.contributor.departmentUniversidad EAFIT. Departamento de Cienciasspa
dc.contributor.researchgroupMatemáticas y Aplicacionesspa
dc.date.accessioned2021-04-12T14:04:24Z
dc.date.available2021-04-12T14:04:24Z
dc.date.issued2020-01-01
dc.description.abstractDengue disease is a major problem for public health surveillance entities in tropical and subtropical regions having a significant impact not only epidemiological but social and economical. There are many factors involved in the dengue transmission process. We can evaluate the importance of these factors through the formulation of mathematical models. However, the majority of the models presented in the literature tend to be overparameterized, with considerable uncertainty levels and excessively complex formulations. We aim to evaluate the structure, complexity, trustworthiness, and suitability of three models, for the transmission of dengue disease, through different strategies. To achieve this goal, we perform structural and practical identifiability, sensitivity and uncertainty analyses to these models. The results showed that the simplest model was the most appropriate and reliable when the only available information to fit them is the cumulative number of reported dengue cases in an endemic municipality of Colombia. © 2020 Lizarralde-Bejarano et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.eng
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=11957
dc.identifier.doi10.1371/journal.pone.0229668
dc.identifier.issn19326203
dc.identifier.otherWOS;000535284700032
dc.identifier.otherPUBMED;32160217
dc.identifier.otherSCOPUS;2-s2.0-85081206480
dc.identifier.urihttps://hdl.handle.net/10784/27726
dc.language.isoeng
dc.publisherPublic Library of Science
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85081206480&doi=10.1371%2fjournal.pone.0229668&partnerID=40&md5=b1c9b3eec1ac2399ad40d3c0f8e8aad0
dc.rightshttps://v2.sherpa.ac.uk/id/publication/issn/1932-6203
dc.sourcePlos One
dc.subject.keywordArticleeng
dc.subject.keywordColombiaeng
dc.subject.keyworddata analysis softwareeng
dc.subject.keyworddata processingeng
dc.subject.keyworddengueeng
dc.subject.keyworddisease transmissioneng
dc.subject.keywordhumaneng
dc.subject.keywordmathematical modeleng
dc.subject.keywordmethodologyeng
dc.subject.keywordnonhumaneng
dc.subject.keywordreliabilityeng
dc.subject.keywordsensitivity analysiseng
dc.subject.keywordtrusteng
dc.subject.keyworduncertaintyeng
dc.titleSensitivity, uncertainty and identifiability analyses to define a dengue transmission model with real data of an endemic municipality of Colombia
dc.typeinfo:eu-repo/semantics/article
dc.type.coarversionhttp://purl.org/coar/resource_type/c_6501
dc.type.localArtículospa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTREF
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dspace.entity.typePublication

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