Dynamic causal modelling of COVID-19.
Identifieur interne : 000378 ( Main/Corpus ); précédent : 000377; suivant : 000379Dynamic causal modelling of COVID-19.
Auteurs : Karl J. Friston ; Thomas Parr ; Peter Zeidman ; Adeel Razi ; Guillaume Flandin ; Jean Daunizeau ; Ollie J. Hulme ; Alexander J. Billig ; Vladimir Litvak ; Rosalyn J. Moran ; Cathy J. Price ; Christian LambertSource :
- Wellcome open research [ 2398-502X ] ; 2020.
Abstract
This technical report describes a dynamic causal model of the spread of coronavirus through a population. The model is based upon ensemble or population dynamics that generate outcomes, like new cases and deaths over time. The purpose of this model is to quantify the uncertainty that attends predictions of relevant outcomes. By assuming suitable conditional dependencies, one can model the effects of interventions (e.g., social distancing) and differences among populations (e.g., herd immunity) to predict what might happen in different circumstances. Technically, this model leverages state-of-the-art variational (Bayesian) model inversion and comparison procedures, originally developed to characterise the responses of neuronal ensembles to perturbations. Here, this modelling is applied to epidemiological populations-to illustrate the kind of inferences that are supported and how the model per se can be optimised given timeseries data. Although the purpose of this paper is to describe a modelling protocol, the results illustrate some interesting perspectives on the current pandemic; for example, the nonlinear effects of herd immunity that speak to a self-organised mitigation process.
DOI: 10.12688/wellcomeopenres.15881.2
PubMed: 32832701
PubMed Central: PMC7431977
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Friston</name><affiliation><nlm:affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Parr, Thomas" sort="Parr, Thomas" uniqKey="Parr T" first="Thomas" last="Parr">Thomas Parr</name><affiliation><nlm:affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Zeidman, Peter" sort="Zeidman, Peter" uniqKey="Zeidman P" first="Peter" last="Zeidman">Peter Zeidman</name><affiliation><nlm:affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Razi, Adeel" sort="Razi, Adeel" uniqKey="Razi A" first="Adeel" last="Razi">Adeel Razi</name><affiliation><nlm:affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Turner Institute for Brain and Mental Health & Monash Biomedical Imaging, Monash University, Clayton, VIC, 3800, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Flandin, Guillaume" sort="Flandin, Guillaume" uniqKey="Flandin G" first="Guillaume" last="Flandin">Guillaume Flandin</name><affiliation><nlm:affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Daunizeau, Jean" sort="Daunizeau, Jean" uniqKey="Daunizeau J" first="Jean" last="Daunizeau">Jean Daunizeau</name><affiliation><nlm:affiliation>Institut du Cerveau et de la Moelle épinière, INSERM UMRS, Paris, 1127, France.</nlm:affiliation></affiliation></author><author><name sortKey="Hulme, Ollie J" sort="Hulme, Ollie J" uniqKey="Hulme O" first="Ollie J" last="Hulme">Ollie J. Hulme</name><affiliation><nlm:affiliation>Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>London Mathematical Laboratory, Hammersmith, London, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Billig, Alexander J" sort="Billig, Alexander J" uniqKey="Billig A" first="Alexander J" last="Billig">Alexander J. 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Friston</name><affiliation><nlm:affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Parr, Thomas" sort="Parr, Thomas" uniqKey="Parr T" first="Thomas" last="Parr">Thomas Parr</name><affiliation><nlm:affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Zeidman, Peter" sort="Zeidman, Peter" uniqKey="Zeidman P" first="Peter" last="Zeidman">Peter Zeidman</name><affiliation><nlm:affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Razi, Adeel" sort="Razi, Adeel" uniqKey="Razi A" first="Adeel" last="Razi">Adeel Razi</name><affiliation><nlm:affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Turner Institute for Brain and Mental Health & Monash Biomedical Imaging, Monash University, Clayton, VIC, 3800, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Flandin, Guillaume" sort="Flandin, Guillaume" uniqKey="Flandin G" first="Guillaume" last="Flandin">Guillaume Flandin</name><affiliation><nlm:affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Daunizeau, Jean" sort="Daunizeau, Jean" uniqKey="Daunizeau J" first="Jean" last="Daunizeau">Jean Daunizeau</name><affiliation><nlm:affiliation>Institut du Cerveau et de la Moelle épinière, INSERM UMRS, Paris, 1127, France.</nlm:affiliation></affiliation></author><author><name sortKey="Hulme, Ollie J" sort="Hulme, Ollie J" uniqKey="Hulme O" first="Ollie J" last="Hulme">Ollie J. Hulme</name><affiliation><nlm:affiliation>Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>London Mathematical Laboratory, Hammersmith, London, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Billig, Alexander J" sort="Billig, Alexander J" uniqKey="Billig A" first="Alexander J" last="Billig">Alexander J. Billig</name><affiliation><nlm:affiliation>Ear Institute, University College London, London, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Litvak, Vladimir" sort="Litvak, Vladimir" uniqKey="Litvak V" first="Vladimir" last="Litvak">Vladimir Litvak</name><affiliation><nlm:affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Moran, Rosalyn J" sort="Moran, Rosalyn J" uniqKey="Moran R" first="Rosalyn J" last="Moran">Rosalyn J. Moran</name><affiliation><nlm:affiliation>Centre for Neuroimaging Science, Department of Neuroimaging, IoPPN, King's College London, London, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Price, Cathy J" sort="Price, Cathy J" uniqKey="Price C" first="Cathy J" last="Price">Cathy J. Price</name><affiliation><nlm:affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Lambert, Christian" sort="Lambert, Christian" uniqKey="Lambert C" first="Christian" last="Lambert">Christian Lambert</name><affiliation><nlm:affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</nlm:affiliation></affiliation></author></analytic><series><title level="j">Wellcome open research</title><idno type="ISSN">2398-502X</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">This technical report describes a dynamic causal model of the spread of coronavirus through a population. The model is based upon ensemble or population dynamics that generate outcomes, like new cases and deaths over time. The purpose of this model is to quantify the uncertainty that attends predictions of relevant outcomes. By assuming suitable conditional dependencies, one can model the effects of interventions (e.g., social distancing) and differences among populations (e.g., herd immunity) to predict what might happen in different circumstances. Technically, this model leverages state-of-the-art variational (Bayesian) model inversion and comparison procedures, originally developed to characterise the responses of neuronal ensembles to perturbations. Here, this modelling is applied to epidemiological populations-to illustrate the kind of inferences that are supported and how the model <i>per se</i> can be optimised given timeseries data. Although the purpose of this paper is to describe a modelling protocol, the results illustrate some interesting perspectives on the current pandemic; for example, the nonlinear effects of herd immunity that speak to a self-organised mitigation process.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" VersionID="2" VersionDate="2020/08/07" Owner="NLM"><PMID Version="2">32832701</PMID><DateRevised><Year>2020</Year><Month>08</Month><Day>25</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">2398-502X</ISSN><JournalIssue CitedMedium="Print"><Volume>5</Volume><PubDate><Year>2020</Year></PubDate></JournalIssue><Title>Wellcome open research</Title><ISOAbbreviation>Wellcome Open Res</ISOAbbreviation></Journal><ArticleTitle>Dynamic causal modelling of COVID-19.</ArticleTitle><Pagination><MedlinePgn>89</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.12688/wellcomeopenres.15881.2</ELocationID><Abstract><AbstractText>This technical report describes a dynamic causal model of the spread of coronavirus through a population. The model is based upon ensemble or population dynamics that generate outcomes, like new cases and deaths over time. The purpose of this model is to quantify the uncertainty that attends predictions of relevant outcomes. By assuming suitable conditional dependencies, one can model the effects of interventions (e.g., social distancing) and differences among populations (e.g., herd immunity) to predict what might happen in different circumstances. Technically, this model leverages state-of-the-art variational (Bayesian) model inversion and comparison procedures, originally developed to characterise the responses of neuronal ensembles to perturbations. Here, this modelling is applied to epidemiological populations-to illustrate the kind of inferences that are supported and how the model <i>per se</i> can be optimised given timeseries data. Although the purpose of this paper is to describe a modelling protocol, the results illustrate some interesting perspectives on the current pandemic; for example, the nonlinear effects of herd immunity that speak to a self-organised mitigation process.</AbstractText><CopyrightInformation>Copyright: © 2020 Friston KJ et al.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Friston</LastName><ForeName>Karl J</ForeName><Initials>KJ</Initials><Identifier Source="ORCID">https://orcid.org/0000-0001-7984-8909</Identifier><AffiliationInfo><Affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Parr</LastName><ForeName>Thomas</ForeName><Initials>T</Initials><Identifier Source="ORCID">https://orcid.org/0000-0001-5108-5743</Identifier><AffiliationInfo><Affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zeidman</LastName><ForeName>Peter</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Razi</LastName><ForeName>Adeel</ForeName><Initials>A</Initials><Identifier Source="ORCID">https://orcid.org/0000-0002-0779-9439</Identifier><AffiliationInfo><Affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Turner Institute for Brain and Mental Health & Monash Biomedical Imaging, Monash University, Clayton, VIC, 3800, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Flandin</LastName><ForeName>Guillaume</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Daunizeau</LastName><ForeName>Jean</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Institut du Cerveau et de la Moelle épinière, INSERM UMRS, Paris, 1127, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hulme</LastName><ForeName>Ollie J</ForeName><Initials>OJ</Initials><AffiliationInfo><Affiliation>Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>London Mathematical Laboratory, Hammersmith, London, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Billig</LastName><ForeName>Alexander J</ForeName><Initials>AJ</Initials><Identifier Source="ORCID">https://orcid.org/0000-0002-4531-8616</Identifier><AffiliationInfo><Affiliation>Ear Institute, University College London, London, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Litvak</LastName><ForeName>Vladimir</ForeName><Initials>V</Initials><AffiliationInfo><Affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Moran</LastName><ForeName>Rosalyn J</ForeName><Initials>RJ</Initials><Identifier Source="ORCID">https://orcid.org/0000-0002-2736-2621</Identifier><AffiliationInfo><Affiliation>Centre for Neuroimaging Science, Department of Neuroimaging, IoPPN, King's College London, London, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Price</LastName><ForeName>Cathy J</ForeName><Initials>CJ</Initials><AffiliationInfo><Affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lambert</LastName><ForeName>Christian</ForeName><Initials>C</Initials><Identifier Source="ORCID">https://orcid.org/0000-0001-8281-4611</Identifier><AffiliationInfo><Affiliation>Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><DataBankList CompleteYN="Y"><DataBank><DataBankName>figshare</DataBankName><AccessionNumberList><AccessionNumber>10.6084/m9.figshare.12174006.v1</AccessionNumber></AccessionNumberList></DataBank></DataBankList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>08</Month><Day>07</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Wellcome Open Res</MedlineTA><NlmUniqueID>101696457</NlmUniqueID><ISSNLinking>2398-502X</ISSNLinking></MedlineJournalInfo><KeywordList 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