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Barbarossa, M.V.* ; Fuhrmann, J.* ; Meinke, J.H.* ; Krieg, S.* ; Varma, H.V.* ; Castelletti, N. ; Lippert, T.*

Modeling the spread of COVID-19 in Germany: Early assessment and possible scenarios.

PLoS ONE 15:e0238559 (2020)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
The novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe with about 2.2 million confirmed cases and more than 150,000 deaths as of April 17, 2020. In this work, mathematical models are used to reproduce data of the early evolution of the COVID-19 outbreak in Germany, taking into account the effect of actual and hypothetical non-pharmaceutical interventions. Systems of differential equations of SEIR type are extended to account for undetected infections, stages of infection, and age groups. The models are calibrated on data until April 5. Data from April 6 to 14 are used for model validation. We simulate different possible strategies for the mitigation of the current outbreak, slowing down the spread of the virus and thus reducing the peak in daily diagnosed cases, the demand for hospitalization or intensive care units admissions, and eventually the number of fatalities. Our results suggest that a partial (and gradual) lifting of introduced control measures could soon be possible if accompanied by further increased testing activity, strict isolation of detected cases, and reduced contact to risk groups.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Coronavirus; Transmission; Wuhan
ISSN (print) / ISBN 1932-6203
Zeitschrift PLoS ONE
Quellenangaben Band: 15, Heft: 9, Seiten: , Artikelnummer: e0238559 Supplement: ,
Verlag Public Library of Science (PLoS)
Verlagsort Lawrence, Kan.
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Radiation Medicine (IRM)
Förderungen LOEWE focus Center for Multiscale Modelling in Life Sciences (CMMS)