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dc.contributor.author
Wu, Ke
dc.contributor.author
Darcet, Didier
dc.contributor.author
Wang, Qian
dc.contributor.author
Sornette, Didier
dc.date.accessioned
2020-10-16T12:24:50Z
dc.date.available
2020-09-04T19:59:11Z
dc.date.available
2020-09-07T13:19:11Z
dc.date.available
2020-10-16T12:24:50Z
dc.date.issued
2020-08
dc.identifier.issn
0924-090X
dc.identifier.issn
1573-269X
dc.identifier.other
10.1007/s11071-020-05862-6
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/438557
dc.identifier.doi
10.3929/ethz-b-000438557
dc.description.abstract
Started in Wuhan, China, the COVID-19 has been spreading all over the world. We calibrate the logistic growth model, the generalized logistic growth model, the generalized Richards model and the generalized growth model to the reported number of infected cases for the whole of China, 29 provinces in China, and 33 countries and regions that have been or are undergoing major outbreaks. We dissect the development of the epidemics in China and the impact of the drastic control measures both at the aggregate level and within each province. We quantitatively document four phases of the outbreak in China with a detailed analysis on the heterogeneous situations across provinces. The extreme containment measures implemented by China were very effective with some instructive variations across provinces. Borrowing from the experience of China, we made scenario projections on the development of the outbreak in other countries. We identified that outbreaks in 14 countries (mostly in western Europe) have ended, while resurgences of cases have been identified in several among them. The modeling results clearly show longer after-peak trajectories in western countries, in contrast to most provinces in China where the after-peak trajectory is characterized by a much faster decay. We identified three groups of countries in different level of outbreak progress, and provide informative implications for the current global pandemic.
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
Novel coronavirus (COVID-19)
en_US
dc.subject
Logistic growing
en_US
dc.subject
Epidemic modeling
en_US
dc.subject
Prediction
en_US
dc.title
Generalized logistic growth modeling of the COVID-19 outbreak: comparing the dynamics in the 29 provinces in China and in the rest of the world
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2020-08-19
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
1561
en_US
ethz.pages.end
1581
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Dortrecht
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
2020-09-04T19:59:20Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2020-10-16T12:25:02Z
ethz.rosetta.lastUpdated
2021-02-15T18:25:41Z
ethz.rosetta.versionExported
true
ethz.COinS
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