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Modeling the spread of COVID-19 in Germany: Early assessment and possible scenarios.
PLoS ONE 15:e0238559 (2020)
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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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Coronavirus; Transmission; Wuhan
Language
english
Publication Year
2020
HGF-reported in Year
2020
ISSN (print) / ISBN
1932-6203
Journal
PLoS ONE
Quellenangaben
Volume: 15,
Issue: 9,
Article Number: e0238559
Publisher
Public Library of Science (PLoS)
Publishing Place
Lawrence, Kan.
Reviewing status
Peer reviewed
Institute(s)
Institute of Radiation Medicine (IRM)
POF-Topic(s)
30203 - Molecular Targets and Therapies
Research field(s)
Radiation Sciences
PSP Element(s)
G-501391-001
Grants
LOEWE focus Center for Multiscale Modelling in Life Sciences (CMMS)
WOS ID
WOS:000571064300005
Scopus ID
85090506502
PubMed ID
32886696
Erfassungsdatum
2020-10-29