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dc.contributor.authorAguiar, M. 
dc.contributor.authorBidaurrazagaVan‑Dierdonc, J.
dc.contributor.authorMar, J.
dc.contributor.authorCusimano, N. 
dc.contributor.authorKnopoff, D.A. 
dc.contributor.authorAnam, V. 
dc.contributor.authorStollenwerk, N. 
dc.date.accessioned2021-07-06T17:06:58Z
dc.date.available2021-07-06T17:06:58Z
dc.date.issued2021-07-06
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/20.500.11824/1304
dc.description.abstractAs the COVID-19 pandemic progressed, research on mathematical modeling became imperative and very influential to understand the epidemiological dynamics of disease spreading. The momentary reproduction ratio r(t) of an epidemic is used as a public health guiding tool to evaluate the course of the epidemic, with the evolution of r(t) being the reasoning behind tightening and relaxing control measures over time. Here we investigate critical fluctuations around the epidemiological threshold, resembling new waves, even when the community disease transmission rate β is not signifcantly changing. Without loss of generality, we use simple models that can be treated analytically and results are applied to more complex models describing COVID-19 epidemics. Our analysis shows that, rather than the supercritical regime (infectivity larger than a critical value, β>βc) leading to new exponential growth of infection, the subcritical regime (infectivity smaller than a critical value, β<βc) with small import is able to explain the dynamic behaviour of COVID-19 spreading after a lockdown lifting, with r(t) ≈ 1 hovering around its threshold value.en_US
dc.description.sponsorshipBMTF “Mathematical Modeling Applied to Health” Project European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 792494en_US
dc.formatapplication/pdfen_US
dc.language.isoengen_US
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/en_US
dc.subjectCOVID-19en_US
dc.subjectSTOCHASTIC FLUCTUATIONSen_US
dc.subjectMATHEMATICAL MODELINGen_US
dc.subjectLOCKDOWNen_US
dc.titleCritical fluctuations in epidemic models explain COVID‑19 post‑lockdown dynamicsen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.relation.publisherversionhttps://rdcu.be/cnKR7en_US
dc.relation.projectIDES/1PE/SEV-2017-0718en_US
dc.relation.projectIDEUS/BERC/BERC.2018-2021en_US
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen_US
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersionen_US
dc.journal.titleNature Scientific Reportsen_US


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Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España