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dc.contributor.authorPriesemann, Viola
dc.contributor.authorMeyer-Hermann, Michael
dc.contributor.authorPigeot, Iris
dc.contributor.authorSchöbel, Anita
dc.date.accessioned2021-10-04T14:27:18Z
dc.date.available2021-10-04T14:27:18Z
dc.date.issued2021-07-30
dc.identifier.citationBundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2021 Sep;64(9):1058-1066. German. doi: 10.1007/s00103-021-03390-1. Epub 2021 Jul 30.en_US
dc.identifier.pmid34328524
dc.identifier.doi10.1007/s00103-021-03390-1
dc.identifier.urihttp://hdl.handle.net/10033/623060
dc.description.abstractAfter the global outbreak of the COVID-19 pandemic, an infection dynamic of immense extent developed. Since then, numerous measures have been taken to bring the infection under control. This was very successful in the spring of 2020, while the number of infections rose sharply the following autumn. To predict the occurrence of infections, epidemiological models are used. These are in principle a very valuable tool in pandemic management. However, they still partly need to be based on assumptions regarding the transmission routes and possible drivers of the infection dynamics. Despite numerous individual approaches, systematic epidemiological data are still lacking with which, for example, the effectiveness of individual measures could be quantified. Such information generated in studies is needed to enable reliable predictions regarding the further course of the pandemic. Thereby, the complexity of the models could develop hand in hand with the complexity of the available data. In this article, after delineating two basic classes of models, the contribution of epidemiological models to the assessment of various central aspects of the pandemic, such as the reproduction rate, the number of unreported cases, infection fatality rate, and the consideration of regionality, is shown. Subsequently, the use of the models to quantify the impact of measures and the effects of the "test-trace-isolate" strategy is described. In the concluding discussion, the limitations of such modelling approaches are juxtaposed with their advantages.en_US
dc.language.isodeen_US
dc.publisherSpringeren_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectAgent-based modelsen_US
dc.subjectCompartmental modelsen_US
dc.subjectDark figureen_US
dc.subjectInfection fatality rateen_US
dc.subjectReproductive numberen_US
dc.title[The contribution of epidemiological models to the description of the outbreak of the COVID-19 pandemic].en_US
dc.typeReviewen_US
dc.identifier.eissn1437-1588
dc.contributor.departmentHZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany.en_US
dc.identifier.journalBundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutzen_US
dc.source.volume64
dc.source.issue9
dc.source.beginpage1058
dc.source.endpage1066
refterms.dateFOA2021-10-04T14:27:18Z
dc.source.journaltitleBundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
dc.source.countryGermany


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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International