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dc.contributor.authorMoriña, David
dc.contributor.authorFernandez Fontelo, Amanda
dc.contributor.authorCabaña Nigro, Ana Alejandra
dc.contributor.authorArratia Quesada, Argimiro Alejandro
dc.contributor.authorÁvalos Villaseñor, Gustavo Eduardo
dc.contributor.authorPuig, Pedro
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Computació
dc.date.accessioned2021-07-15T10:39:54Z
dc.date.available2021-12-28T01:27:16Z
dc.date.issued2021-06-28
dc.identifier.citationMoriña, D. [et al.]. Cumulated burden of Covid-19 in Spain from a Bayesian perspective. "European journal of public health", 28 Juny 2021, p. 1-11.
dc.identifier.issn1101-1262
dc.identifier.urihttp://hdl.handle.net/2117/349412
dc.description.abstractBackground The main goal of this work is to estimate the actual number of cases of Covid-19 in Spain in the period 01-31-2020/06-01-2020 by Autonomous Communities. Based on these estimates, this work allows us to accurately re-estimate the lethality of the disease in Spain, taking into account unreported cases. Methods A hierarchical Bayesian model recently proposed in the literature has been adapted to model the actual number of Covid-19 cases in Spain. Results The results of this work show that the real load of Covid-19 in Spain in the period considered is well above the data registered by the public health system. Specifically, the model estimates show that, cumulatively until June 1st, 2020, there were 2 425 930 cases of Covid-19 in Spain with characteristics similar to those reported (95% credibility interval: 2 148 261 2 813 864), from which were actually registered only 518 664. Conclusions Considering the results obtained from the second wave of the Spanish seroprevalence study, which estimates 2 350 324 cases of Covid-19 produced in Spain, in the period of time considered, it can be seen that the estimates provided by the model are quite good. This work clearly shows the key importance of having good quality data to optimize decision-making in the critical context of dealing with a pandemic.
dc.format.extent11 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Ciències de la salut::Medicina::Medicina comunitària i salut pública
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística aplicada::Estadística biosanitària
dc.subject.lcshCOVID-19 (Disease)
dc.subject.lcshPublic health
dc.subject.lcshBayesian statistical decision theory
dc.subject.otherCovid-19
dc.subject.otherBayesian methods
dc.subject.otherPublic health
dc.subject.otherInfections
dc.subject.otherUnderreporting
dc.titleCumulated burden of Covid-19 in Spain from a Bayesian perspective
dc.typeArticle
dc.subject.lemacCOVID-19 (Malaltia)
dc.subject.lemacSalut pública
dc.subject.lemacEstadística bayesiana
dc.contributor.groupUniversitat Politècnica de Catalunya. SOCO - Soft Computing
dc.identifier.doi10.1093/eurpub/ckab118
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://academic.oup.com/eurpub/advance-article/doi/10.1093/eurpub/ckab118/6310740
dc.rights.accessOpen Access
local.identifier.drac31871721
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/TIN2017-89244-R
local.citation.authorMoriña, D.; Fernandez, A.; Cabaña, A.; Arratia, A.; Avalos, G.; Puig, P.
local.citation.publicationNameEuropean journal of public health
local.citation.startingPage1
local.citation.endingPage11


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