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dc.contributor.author
Wang, Ziqi
dc.contributor.author
Broccardo, Marco
dc.contributor.author
Mignan, Arnaud
dc.contributor.author
Sornette, Didier
dc.date.accessioned
2020-10-16T14:11:53Z
dc.date.available
2020-09-23T02:41:58Z
dc.date.available
2020-09-24T14:32:08Z
dc.date.available
2020-10-16T14:11:53Z
dc.date.issued
2020-08
dc.identifier.issn
0924-090X
dc.identifier.issn
1573-269X
dc.identifier.other
10.1007/s11071-020-05871-5
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/441997
dc.identifier.doi
10.3929/ethz-b-000441997
dc.description.abstract
With the unfolding of the COVID-19 pandemic, mathematical modelling of epidemics has been perceived and used as a central element in understanding, predicting, and governing the pandemic event. However, soon it became clear that long-term predictions were extremely challenging to address. In addition, it is still unclear which metric shall be used for a global description of the evolution of the outbreaks. Yet a robust modelling of pandemic dynamics and a consistent choice of the transmission metric is crucial for an in-depth understanding of the macroscopic phenomenology and better-informed mitigation strategies. In this study, we propose a Markovian stochastic framework designed for describing the evolution of entropy during the COVID-19 pandemic together with the instantaneous reproductive ratio. Then, we introduce and use entropy-based metrics of global transmission to measure the impact and the temporal evolution of a pandemic event. In the formulation of the model, the temporal evolution of the outbreak is modelled by an equation governing the probability distribution that describes a nonlinear Markov process of a statistically averaged individual, leading to a clear physical interpretation. The time-dependent parameters are formulated by adaptive basis functions, leading to a parsimonious representation. In addition, we provide a full Bayesian inversion scheme for calibration together with a coherent strategy to address data unreliability. The time evolution of the entropy rate, the absolute change in the system entropy, and the instantaneous reproductive ratio are natural and transparent outputs of this framework. The framework has the appealing property of being applicable to any compartmental epidemic model. As an illustration, we apply the proposed approach to a simple modification of the susceptible–exposed–infected–removed model. Applying the model to the Hubei region, South Korean, Italian, Spanish, German, and French COVID-19 datasets, we discover significant difference in the absolute change of entropy but highly regular trends for both the entropy evolution and the instantaneous reproductive ratio.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Springer
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
COVID-19
en_US
dc.subject
Nonlinear Markov process
en_US
dc.subject
Stochastic process
en_US
dc.subject
Uncertainty quantification
en_US
dc.subject
Bayesian analysis
en_US
dc.title
The dynamics of entropy in the COVID-19 outbreaks
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2020-09-09
ethz.journal.title
Nonlinear Dynamics
ethz.journal.volume
101
en_US
ethz.journal.issue
3
en_US
ethz.journal.abbreviated
Nonlinear dyn.
ethz.pages.start
1847
en_US
ethz.pages.end
1869
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Berlin
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03738 - Sornette, Didier / Sornette, Didier
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03738 - Sornette, Didier / Sornette, Didier
ethz.date.deposited
2020-09-23T02:42:09Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2020-10-16T14:12:04Z
ethz.rosetta.lastUpdated
2021-02-15T18:26:19Z
ethz.rosetta.versionExported
true
ethz.COinS
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