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dc.contributor.authorCassini, Alessandro
dc.contributor.authorHögberg, Liselotte Diaz
dc.contributor.authorPlachouras, Diamantis
dc.contributor.authorQuattrocchi, Annalisa
dc.contributor.authorHoxha, Ana
dc.contributor.authorSimonsen, Gunnar Skov
dc.contributor.authorColomb-Cotinat, Mélanie
dc.contributor.authorKretzschmar, Mirjam E.
dc.contributor.authorDevleesschauwer, Brecht
dc.contributor.authorCecchini, Michele
dc.contributor.authorOuakrim, Driss Ait
dc.contributor.authorOliveira, Tiago Cravo
dc.contributor.authorStruelens, Marc J.
dc.contributor.authorSuetens, Carl
dc.contributor.authorMonnet, Dominique L.
dc.date.accessioned2020-03-05T11:35:33Z
dc.date.available2020-03-05T11:35:33Z
dc.date.issued2018-11-05
dc.description.abstract<i>Background</i> - Infections due to antibiotic-resistant bacteria are threatening modern health care. However, estimating their incidence, complications, and attributable mortality is challenging. We aimed to estimate the burden of infections caused by antibiotic-resistant bacteria of public health concern in countries of the EU and European Economic Area (EEA) in 2015, measured in number of cases, attributable deaths, and disability-adjusted life-years (DALYs).<p><p> <i>Methods</i> - We estimated the incidence of infections with 16 antibiotic resistance–bacterium combinations from European Antimicrobial Resistance Surveillance Network (EARS-Net) 2015 data that was country-corrected for population coverage. We multiplied the number of bloodstream infections (BSIs) by a conversion factor derived from the European Centre for Disease Prevention and Control point prevalence survey of health-care-associated infections in European acute care hospitals in 2011–12 to estimate the number of non-BSIs. We developed disease outcome models for five types of infection on the basis of systematic reviews of the literature.<p><p> <i>Findings</i> - From EARS-Net data collected between Jan 1, 2015, and Dec 31, 2015, we estimated 671 689 (95% uncertainty interval [UI] 583 148–763 966) infections with antibiotic-resistant bacteria, of which 63·5% (426 277 of 671 689) were associated with health care. These infections accounted for an estimated 33 110 (28 480–38 430) attributable deaths and 874 541 (768 837–989 068) DALYs. The burden for the EU and EEA was highest in infants (aged <1 year) and people aged 65 years or older, had increased since 2007, and was highest in Italy and Greece.<p><p> <i>Interpretation</i> - Our results present the health burden of five types of infection with antibiotic-resistant bacteria expressed, for the first time, in DALYs. The estimated burden of infections with antibiotic-resistant bacteria in the EU and EEA is substantial compared with that of other infectious diseases, and has increased since 2007. Our burden estimates provide useful information for public health decision-makers prioritising interventions for infectious diseases.<p><p> <i>Funding</i> - European Centre for Disease Prevention and Control.en_US
dc.identifier.citationCassini, Högberg LD, Plachouras D, Quattrocchi, Hoxha, Simonsen GS, Colomb-Cotinat, Kretzschmar ME, Devleesschauwer B, Cecchini, Ouakrim, Oliveira TC, Struelens MJ, Suetens C, Monnet DL. Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysis. Lancet. Infectious Diseases (Print). 2019;19(1):56-66en_US
dc.identifier.cristinIDFRIDAID 1690650
dc.identifier.doi10.1016/S1473-3099(18)30605-4
dc.identifier.issn1473-3099
dc.identifier.issn1474-4457
dc.identifier.urihttps://hdl.handle.net/10037/17640
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.journalLancet. Infectious Diseases (Print)
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2018 The Author(s)en_US
dc.subjectVDP::Medical disciplines: 700en_US
dc.subjectVDP::Medisinske Fag: 700en_US
dc.titleAttributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysisen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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