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Epidemiological Forecasting with Model Reduction of Compartmental Models. Application to the COVID-19 Pandemic

hal.structure.identifierService de Thermo-hydraulique et de Mécanique des Fluides [STMF]
hal.structure.identifierCentre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique [CERMICS]
dc.contributor.authorBakhta, Athmane
hal.structure.identifierCentre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique [CERMICS]
dc.contributor.authorBoiveau, Thomas
hal.structure.identifierLaboratoire Jacques-Louis Lions [LJLL (UMR_7598)]
dc.contributor.authorMaday, Yvon
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorMula, Olga
HAL ID: 1531
ORCID: 0000-0002-3017-6598
dc.date.accessioned2021-10-26T12:42:59Z
dc.date.available2021-10-26T12:42:59Z
dc.date.issued2021
dc.identifier.issn2079-7737
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/22104
dc.language.isoenen
dc.subjectCOVID-19en
dc.subjectReduced basisen
dc.subjectEpidemiologyen
dc.subjectForecastingen
dc.subjectModel reductionen
dc.subject.ddc520en
dc.titleEpidemiological Forecasting with Model Reduction of Compartmental Models. Application to the COVID-19 Pandemicen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenWe propose a forecasting method for predicting epidemiological health series on a two-week horizon at regional and interregional resolution. The approach is based on the model orderreduction of parametric compartmental models and is designed to accommodate small amounts ofsanitary data. The efficiency of the method is shown in the case of the prediction of the number ofinfected people and people removed from the collected data, either due to death or recovery, duringthe two pandemic waves of COVID-19 in France, which took place approximately between Februaryand November 2020. Numerical results illustrate the promising potential of the approachen
dc.relation.isversionofjnlnameBiology
dc.relation.isversionofjnlvol10en
dc.relation.isversionofjnlissue1en
dc.relation.isversionofjnldate2021-12
dc.relation.isversionofjnlpages22en
dc.relation.isversionofdoi10.3390/biology10010022en
dc.identifier.urlsitehttps://hal.sorbonne-universite.fr/hal-03117258en
dc.relation.isversionofjnlpublisherMDPIen
dc.subject.ddclabelSciences connexes (physique, astrophysique)en
dc.relation.forthcomingnonen
dc.description.ssrncandidatenon
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewedouien
dc.date.updated2021-10-26T12:37:30Z
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