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A real-time regional model for COVID-19: Probabilistic situational awareness and forecasting

dc.contributor.authorEngebretsen, Solveig
dc.contributor.authorPalomares, Alfonso Diz-Lois
dc.contributor.authorRø, Gunnar
dc.contributor.authorKristoffersen, Anja Bråthen
dc.contributor.authorLindstrøm, Jonas Christoffer
dc.contributor.authorEngø-Monsen, Kenth
dc.contributor.authorKamineni, Meghana
dc.contributor.authorChan, Yat Hin
dc.contributor.authorDale, Ørjan
dc.contributor.authorMidtbø, Jørgen E.
dc.contributor.authorStenerud, Kristian Lindalen
dc.contributor.authorDi Ruscio, Francesco
dc.contributor.authorWhite, Richard Aubrey
dc.contributor.authorFrigessi, Arnoldo
dc.contributor.authorDe Blasio, Birgitte Freiesleben
dc.date.accessioned2023-04-28T09:13:17Z
dc.date.available2023-04-28T09:13:17Z
dc.date.created2023-02-16T13:46:49Z
dc.date.issued2023
dc.identifier.citationPLoS Computational Biology. 2023, 19:e1010860 (1), 1-26.
dc.identifier.issn1553-734X
dc.identifier.urihttps://hdl.handle.net/11250/3065454
dc.language.isoeng
dc.titleA real-time regional model for COVID-19: Probabilistic situational awareness and forecasting
dc.title.alternativeA real-time regional model for COVID-19: Probabilistic situational awareness and forecasting
dc.typePeer reviewed
dc.typeJournal article
dc.description.versionpublishedVersion
dc.source.pagenumber1-26
dc.source.volume19:e1010860
dc.source.journalPLoS Computational Biology
dc.source.issue1
dc.identifier.doi10.1371/journal.pcbi.1010860
dc.identifier.cristin2126676
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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