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dc.creatorCrespo Márquez, Adolfoes
dc.creatorSIM Research Group (ETSI. University of Seville)es
dc.date.accessioned2020-04-17T19:24:08Z
dc.date.available2020-04-17T19:24:08Z
dc.date.issued2020-04
dc.identifier.citationCrespo Márquez, A. y SIM Research Group (ETSI. University of Seville), (2020). A COVID-19 Recovery Strategy Based on the Health System Capacity Modeling. Implications on Citizen Self-management. Computers & Industrial Engineering
dc.identifier.issn0360-8352es
dc.identifier.urihttps://hdl.handle.net/11441/95407
dc.descriptionVersión preprint depositada sin articulo publicado dada la actualidad del tema. *Solicitud de los autoreses
dc.description.abstractConfinement ends, and recovery phase should be accurate planned. Health System (HS) capacity, specially ICUs and plants capacity and availability, will remain the key stone in this new Covid-19 pandemic life cycle phase. Until massive vaccination programs will be a real option (vaccine developed, world wield production capacity and effective and efficient administration process), date that will mark recovery phase end, important decisions should be taken. Not only by authorities. Citizen self-management and organizations self-management will be crucial. This means: citizen and organizations day a day decision in order to control their own risks (infecting others and being infected). This paper proposes a management tool that is based on a ICUs and plants capacity model. Principal outputs of this tool are, by sequential order and by last best data available: (i) ICUs and plants saturation estimation data (according to incoming rate of patients), (ii) with this results new local and temporal confinement measure can be planned and also a dynamic analysis can be done to estimate maximum Ro saturation scenarios, and finally (iii) provide citizen with clear and accurate data allow them adapting their behavior to authorities’ previous recommendations. One common objective: to accelerate as much as possible socioeconomic normalization with a strict control over HS relapses risk.es
dc.formatapplication/pdfes
dc.format.extent18 p.es
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofComputers & Industrial Engineering
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectHealth systemes
dc.subjectCapacity planninges
dc.subjectCovid-19 recoveryes
dc.subjectQueue theoryes
dc.subjectSimulationes
dc.subjectSystem Dynamicses
dc.subjectCitizen Self-management
dc.titleA COVID-19 Recovery Strategy Based on the Health System Capacity Modeling. Implications on Citizen Self-managementes
dc.typeinfo:eu-repo/semantics/articlees
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessrightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Organización Industrial y Gestión de Empresas Ies
dc.contributor.groupUniversidad de Sevilla. TEP134: Organizacion Industriales
dc.journaltitleComputers & Industrial Engineeringes

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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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