Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/120343
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dc.contributor.authorSaavedra, Pedroen_US
dc.contributor.authorSantana, Angeloen_US
dc.contributor.authorPeñate, Alejandroen_US
dc.contributor.authorHerrera, Carolen_US
dc.contributor.authorPacheco, José M.en_US
dc.date.accessioned2023-02-01T08:44:08Z-
dc.date.available2023-02-01T08:44:08Z-
dc.date.issued2022en_US
dc.identifier.issn2045-2322en_US
dc.identifier.otherScopus-
dc.identifier.urihttp://hdl.handle.net/10553/120343-
dc.description.abstractThe emergence of SARS-CoV-2 in China in December 2019 has posed a major challenge to health systems in all countries around the world. One of the most relevant epidemiological measures to consider during the course of a pandemic is the proportion of cases that eventually die from the disease (case fatality ratio, CFR). Monitoring the evolution of this indicator is of paramount importance because it allows for the assessment of both variations in the lethality of the virus and the effectiveness of the control measures implemented by health authorities. One of the problems with estimating the CFR in practice is that the available data only show daily or weekly counts of new cases and deaths; there is no information on when each deceased patient was infected and therefore it is not possible to know exactly how many cases there were at the time the patient became infected. Various approaches have been proposed for calculating the CFR by correcting for the time lag between infection and death. In this paper, we present a novel methodology to perform a non-parametric estimation of the evolution of the CFR by initially identifying an optimal time lag between infections and deaths. The goodness of this procedure is assessed by means of a simulation study and the method is applied to the estimation of the CFR in Spain in the period from July 2020 to March 2022.en_US
dc.languageengen_US
dc.relation.ispartofScientific Reportsen_US
dc.sourceScientific Reports [EISSN 2045-2322], v. 12 (1), 22052, (Diciembre 2022)en_US
dc.subjectInvestigaciónen_US
dc.titleEvolution of the lethality due to SARS-CoV-2 in Spain according to age group and sexen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1038/s41598-022-25635-yen_US
dc.identifier.scopus85144541792-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.authorscopusid57758277800-
dc.contributor.authorscopusid57726830600-
dc.contributor.authorscopusid58025884200-
dc.contributor.authorscopusid58026674000-
dc.contributor.authorscopusid24741104100-
dc.identifier.eissn2045-2322-
dc.identifier.issue1-
dc.relation.volume12en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.utils.revisionen_US
dc.date.coverdateDiciembre 2022en_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-INFen_US
dc.description.sjr0,973
dc.description.jcr4,6
dc.description.sjrqQ1
dc.description.jcrqQ2
dc.description.scieSCIE
dc.description.miaricds10,5
item.grantfulltextopen-
item.fulltextCon texto completo-
crisitem.author.deptGIR Estadística-
crisitem.author.deptDepartamento de Matemáticas-
crisitem.author.deptGIR Estadística-
crisitem.author.deptDepartamento de Matemáticas-
crisitem.author.orcid0000-0003-1681-7165-
crisitem.author.orcid0000-0002-6513-4814-
crisitem.author.orcid0000-0003-4027-8608-
crisitem.author.parentorgDepartamento de Matemáticas-
crisitem.author.parentorgDepartamento de Matemáticas-
crisitem.author.fullNameSaavedra Santana, Pedro-
crisitem.author.fullNameSantana Del Pino, Ángelo-
crisitem.author.fullNamePacheco Castelao, José Miguel-
Colección:Artículos
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