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dc.contributor.authorDe la Sen Parte, Manuel ORCID
dc.contributor.authorNistal Riobello, Raúl ORCID
dc.contributor.authorIbeas Hernández, Asier ORCID
dc.contributor.authorGarrido Hernández, Aitor Josu ORCID
dc.date.accessioned2020-05-28T21:10:43Z
dc.date.available2020-05-28T21:10:43Z
dc.date.issued2020-05-09
dc.identifier.citationEntropy 22(5) : (2020) // Article ID 534es_ES
dc.identifier.issn1099-4300
dc.identifier.urihttp://hdl.handle.net/10810/43612
dc.description.abstractThis paper studies the representation of a general epidemic model by means of a first-order differential equation with a time-varying log-normal type coefficient. Then the generalization of the first-order differential system to epidemic models with more subpopulations is focused on by introducing the inter-subpopulations dynamics couplings and the control interventions information through the mentioned time-varying coefficient which drives the basic differential equation model. It is considered a relevant tool the control intervention of the infection along its transient to fight more efficiently against a potential initial exploding transmission. The study is based on the fact that the disease-free and endemic equilibrium points and their stability properties depend on the concrete parameterization while they admit a certain design monitoring by the choice of the control and treatment gains and the use of feedback information in the corresponding control interventions. Therefore, special attention is paid to the evolution transients of the infection curve, rather than to the equilibrium points, in terms of the time instants of its first relative maximum towards its previous inflection time instant. Such relevant time instants are evaluated via the calculation of an “ad hoc” Shannon’s entropy. Analytical and numerical examples are included in the study in order to evaluate the study and its conclusions.es_ES
dc.description.sponsorshipThis research was funded by MCIU/AEI/FEDER, UE, grant number RTI2018-094902-B-C22 and the APC was funded by RTI2018-094902-B-C22.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subjectShannon entropyes_ES
dc.subjectepidemic modeles_ES
dc.subjecttransient behaviores_ES
dc.subjectvaccination and treatment intervention controlses_ES
dc.titleOn the Use of Entropy Issues to Evaluate and Control the Transients in Some Epidemic Modelses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.date.updated2020-05-28T14:07:40Z
dc.rights.holder2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).es_ES
dc.relation.publisherversionhttps://www.mdpi.com/1099-4300/22/5/534/htmes_ES
dc.identifier.doi10.3390/e22050534
dc.departamentoesElectricidad y electrónica
dc.departamentoesIngeniería de sistemas y automática
dc.departamentoeuElektrizitatea eta elektronika
dc.departamentoeuSistemen ingeniaritza eta automatika


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2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).