Modeling the spread of COVID-19 in Germany: Early assessment and possible scenarios.
Identifieur interne : 000344 ( Main/Corpus ); précédent : 000343; suivant : 000345Modeling the spread of COVID-19 in Germany: Early assessment and possible scenarios.
Auteurs : Maria Vittoria Barbarossa ; Jan Fuhrmann ; Jan H. Meinke ; Stefan Krieg ; Hridya Vinod Varma ; Noemi Castelletti ; Thomas LippertSource :
- PloS one [ 1932-6203 ] ; 2020.
English descriptors
- KwdEn :
- Adolescent (MeSH), Adult (MeSH), Age Factors (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), Child (MeSH), Child, Preschool (MeSH), Communicable Disease Control (methods), Communicable Disease Control (statistics & numerical data), Coronavirus Infections (epidemiology), Coronavirus Infections (prevention & control), Coronavirus Infections (transmission), Disease Transmission, Infectious (statistics & numerical data), Germany (epidemiology), Hospitalization (statistics & numerical data), Humans (MeSH), Infant (MeSH), Middle Aged (MeSH), Models, Theoretical (MeSH), Pandemics (prevention & control), Pneumonia, Viral (epidemiology), Pneumonia, Viral (prevention & control), Pneumonia, Viral (transmission).
- MESH :
- geographic , epidemiology : Germany.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- methods : Communicable Disease Control.
- prevention & control : Coronavirus Infections, Pandemics, Pneumonia, Viral.
- statistics & numerical data : Communicable Disease Control, Disease Transmission, Infectious, Hospitalization.
- transmission : Coronavirus Infections, Pneumonia, Viral.
- Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Child, Child, Preschool, Humans, Infant, Middle Aged, Models, Theoretical.
Abstract
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.
DOI: 10.1371/journal.pone.0238559
PubMed: 32886696
PubMed Central: PMC7473552
Links to Exploration step
pubmed:32886696Le document en format XML
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Meinke</name><affiliation><nlm:affiliation>Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Krieg, Stefan" sort="Krieg, Stefan" uniqKey="Krieg S" first="Stefan" last="Krieg">Stefan Krieg</name><affiliation><nlm:affiliation>Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Varma, Hridya Vinod" sort="Varma, Hridya Vinod" uniqKey="Varma H" first="Hridya Vinod" last="Varma">Hridya Vinod Varma</name><affiliation><nlm:affiliation>Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Castelletti, Noemi" sort="Castelletti, Noemi" uniqKey="Castelletti N" first="Noemi" last="Castelletti">Noemi Castelletti</name><affiliation><nlm:affiliation>Institute of Radiation Medicine, Helmholtz Zentrum München, Neuherberg, Germany.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Statistical Consulting Unit StaBLab, Ludwig Maximilian University, München, Germany.</nlm:affiliation></affiliation></author><author><name sortKey="Lippert, Thomas" sort="Lippert, Thomas" uniqKey="Lippert T" first="Thomas" last="Lippert">Thomas Lippert</name><affiliation><nlm:affiliation>Frankfurt Institute of Advanced Studies, Frankfurt, Germany.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Department of Mathematics and Computer Science, Goethe University Frankfurt, Frankfurt, Germany.</nlm:affiliation></affiliation></author></analytic><series><title level="j">PloS one</title><idno type="eISSN">1932-6203</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adolescent (MeSH)</term><term>Adult (MeSH)</term><term>Age Factors (MeSH)</term><term>Aged (MeSH)</term><term>Aged, 80 and over (MeSH)</term><term>Child (MeSH)</term><term>Child, Preschool (MeSH)</term><term>Communicable Disease Control (methods)</term><term>Communicable Disease Control (statistics & numerical data)</term><term>Coronavirus Infections (epidemiology)</term><term>Coronavirus Infections (prevention & control)</term><term>Coronavirus Infections (transmission)</term><term>Disease Transmission, Infectious (statistics & numerical data)</term><term>Germany (epidemiology)</term><term>Hospitalization (statistics & numerical data)</term><term>Humans (MeSH)</term><term>Infant (MeSH)</term><term>Middle Aged (MeSH)</term><term>Models, Theoretical (MeSH)</term><term>Pandemics (prevention & control)</term><term>Pneumonia, Viral (epidemiology)</term><term>Pneumonia, Viral (prevention & control)</term><term>Pneumonia, Viral (transmission)</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Germany</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Communicable Disease Control</term></keywords><keywords scheme="MESH" qualifier="prevention & control" xml:lang="en"><term>Coronavirus Infections</term><term>Pandemics</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Communicable Disease Control</term><term>Disease Transmission, Infectious</term><term>Hospitalization</term></keywords><keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adolescent</term><term>Adult</term><term>Age Factors</term><term>Aged</term><term>Aged, 80 and over</term><term>Child</term><term>Child, Preschool</term><term>Humans</term><term>Infant</term><term>Middle Aged</term><term>Models, Theoretical</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32886696</PMID><DateCompleted><Year>2020</Year><Month>09</Month><Day>17</Day></DateCompleted><DateRevised><Year>2020</Year><Month>09</Month><Day>17</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1932-6203</ISSN><JournalIssue CitedMedium="Internet"><Volume>15</Volume><Issue>9</Issue><PubDate><Year>2020</Year></PubDate></JournalIssue><Title>PloS one</Title><ISOAbbreviation>PLoS One</ISOAbbreviation></Journal><ArticleTitle>Modeling the spread of COVID-19 in Germany: Early assessment and possible scenarios.</ArticleTitle><Pagination><MedlinePgn>e0238559</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0238559</ELocationID><Abstract><AbstractText>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.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Barbarossa</LastName><ForeName>Maria Vittoria</ForeName><Initials>MV</Initials><Identifier Source="ORCID">0000-0001-8788-1709</Identifier><AffiliationInfo><Affiliation>Frankfurt Institute of Advanced Studies, Frankfurt, Germany.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Fuhrmann</LastName><ForeName>Jan</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Frankfurt Institute of Advanced Studies, Frankfurt, Germany.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Meinke</LastName><ForeName>Jan H</ForeName><Initials>JH</Initials><AffiliationInfo><Affiliation>Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Krieg</LastName><ForeName>Stefan</ForeName><Initials>S</Initials><Identifier Source="ORCID">0000-0002-8417-9823</Identifier><AffiliationInfo><Affiliation>Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Varma</LastName><ForeName>Hridya Vinod</ForeName><Initials>HV</Initials><AffiliationInfo><Affiliation>Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Castelletti</LastName><ForeName>Noemi</ForeName><Initials>N</Initials><Identifier Source="ORCID">0000-0002-6598-5352</Identifier><AffiliationInfo><Affiliation>Institute of Radiation Medicine, Helmholtz Zentrum München, Neuherberg, Germany.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Statistical Consulting Unit StaBLab, Ludwig Maximilian University, München, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lippert</LastName><ForeName>Thomas</ForeName><Initials>T</Initials><AffiliationInfo><Affiliation>Frankfurt Institute of Advanced Studies, Frankfurt, Germany.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Mathematics and Computer Science, Goethe University Frankfurt, Frankfurt, Germany.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>09</Month><Day>04</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PLoS One</MedlineTA><NlmUniqueID>101285081</NlmUniqueID><ISSNLinking>1932-6203</ISSNLinking></MedlineJournalInfo><SupplMeshList><SupplMeshName Type="Disease" UI="C000657245">COVID-19</SupplMeshName></SupplMeshList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000367" MajorTopicYN="N">Age 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MajorTopicYN="N">transmission</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D018562" MajorTopicYN="N">Disease Transmission, Infectious</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005858" MajorTopicYN="N" Type="Geographic">Germany</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006760" MajorTopicYN="N">Hospitalization</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007223" MajorTopicYN="N">Infant</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008962" 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