Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/180404
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dc.contributor.advisorPalassini, Matteo-
dc.contributor.authorMeca Montserrat, Adrià-
dc.date.accessioned2021-10-05T13:56:58Z-
dc.date.available2021-10-05T13:56:58Z-
dc.date.issued2021-02-
dc.identifier.urihttp://hdl.handle.net/2445/180404-
dc.descriptionTreballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2021, Tutor: Matteo Palassinica
dc.description.abstractIn this work, we delve into the analysis of the propagation of infectious diseases described by the SIR epidemiological model on networks whose connections change over time. We use a fast dynamic message-passing method to estimate the marginal probabilities that each node in one of these networks is in a given state at a certain time. After testing the validity of the predictions given by this approach, we apply them to the problem of inferring the origin of an epidemic on a dynamic network.ca
dc.format.extent5 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoengca
dc.rightscc-by-nc-nd (c) Meca, 2021-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceTreballs Finals de Grau (TFG) - Física-
dc.subject.classificationMalalties infecciosescat
dc.subject.classificationAnàlisi dinàmica de xarxescat
dc.subject.classificationTreballs de fi de graucat
dc.subject.otherCommunicable diseaseseng
dc.subject.otherDynamic network analysiseng
dc.subject.otherBachelor's theseseng
dc.titleDynamic message-passing approach to epidemic spreadingeng
dc.typeinfo:eu-repo/semantics/bachelorThesisca
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
Appears in Collections:Treballs Finals de Grau (TFG) - Física

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