About: Investigating time, strength, and duration of measures in controlling the spread of COVID-19 using a networked meta-population model

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About: Investigating time, strength, and duration of measures in controlling the spread of COVID-19 using a networked meta-population model Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Investigating time, strength, and duration of measures in controlling the spread of COVID-19 using a networked meta-population model
Creator	Zhang, J Chen, X Han, Zhang, Y Lei, Dong Dong, L Zhang, Jiang Guiqing, Yao Han, Á Xinyue, Chen Yanbo, Zhang Yao, G
Source	Medline; PMC
abstract	Policy makers around the world are facing unprecedented challenges in making decisions on when and what degrees of measures should be implemented to tackle the COVID-19 pandemic. Here, using a nationwide mobile phone dataset, we developed a networked meta-population model to simulate the impact of intervention in controlling the spread of the virus in China by varying the effectiveness of transmission reduction and the timing of intervention start and relaxation. We estimated basic reproduction number and transition probabilities between health states based on reported cases. Our model demonstrates that both the time of initiating an intervention and its effectiveness had a very large impact on controlling the epidemic, and the current Chinese intense social distancing intervention has reduced the impact substantially but would have been even more effective had it started earlier. The optimal duration of the control measures to avoid resurgence was estimated to be 2 months, although would need to be longer under less effective controls. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11071-020-05769-2) contains supplementary material, which is available to authorized users.
has issue date	2020-06-27(xsd:dateTime)
bibo:doi	10.1007/s11071-020-05769-2
bibo:pmid	32836809
has license	no-cc
sha1sum (hex)	d96bcc87ce3b32a791d0792a3d1a93c3c226aae6
schema:url	https://doi.org/10.1007/s11071-020-05769-2
resource representing a document's title	Investigating time, strength, and duration of measures in controlling the spread of COVID-19 using a networked meta-population model
has PubMed Central identifier	PMC7320847
has PubMed identifier	32836809
schema:publication	Nonlinear Dyn
resource representing a document's body	covid:d96bcc87ce3b32a791d0792a3d1a93c3c226aae6#body_text
is schema:about of	named entity 'COVID-19' named entity 'networked' named entity 'MAKERS' named entity 'MEASURES' named entity 'CHALLENGES' named entity 'DEGREES' covid:arg/d96bcc87ce3b32a791d0792a3d1a93c3c226aae6 named entity 'makers' named entity 'making decisions' named entity 'Policy makers' named entity 'COVID-19' named entity 'population model' named entity 'SEIR' named entity 'epidemics' named entity 'epidemic' named entity 'mainland China' named entity 'public health' named entity 'epidemic spread' named entity 'China' named entity 'lockdown' named entity '85%' named entity 'Chongqing' named entity 'Switzerland' named entity 'epidemic' named entity 'data sharing' named entity 'PyTorch' named entity 'reproduction number' named entity 'Hubei Province' named entity 'mobile phone' named entity 'COVID' named entity 'France' named entity 'Wuhan' named entity 'Wuhan' named entity 'reproduction number' named entity 'Baidu' named entity 'social distancing' named entity 'Chinese government' named entity 'Guangzhou' named entity 'initial condition' named entity 'art modeling' named entity '85%' named entity 'World Health Organization' named entity 'virus' named entity 'mobile phone' named entity 'COVID' named entity 'Wuhan' named entity 'reproduction number' named entity 'Wuhan' named entity 'Hubei Province' named entity 'location-based services' named entity 'epidemic' named entity 'epidemic' named entity 'China' named entity 'China' named entity 'Wuhan' named entity 'epidemic' named entity 'Wuhan' named entity 'China' named entity 'human migration' named entity 'crowdsourcing' named entity 'Chinese government' named entity 'Xiaogan' named entity 'January 22' named entity 'COVID-19 virus' named entity 'Wuhan' named entity 'social distancing' named entity 'epidemic' named entity 'quarantine' named entity 'China' named entity 'loss function'

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