About: Impact of media reports on the early spread of COVID-19 epidemic

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Impact of media reports on the early spread of COVID-19 epidemic Goto Sponge NotDistinct Permalink

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Impact of media reports on the early spread of COVID-19 epidemic
Creator	Tang, Sanyi Tang, Y Wang, J Yang, L Yang, X Tang, Yingling Wang, Jiaying Yan, Q Yan, Dingding Yan, Qinling Yang, Linqian Yang, Xinpei Yan, D
topic	covid:e0870a29e3968f2bc9a247c6bf29a9b536403968#this
Source	Elsevier; Medline; PMC
abstract	Media reports can modify people’s knowledge of emerging infectious diseases, and thus changing the public attitudes and behaviors. However, how the media reports affect the development of COVID-19 epidemic is a key public health issue. Here the Pearson correlation and cross-correlation analyses are conducted to find the statistically significant correlations between the number of new hospital notifications for COVID-19 and the number of daily news items for twelve major websites in China from January 11th to February 6th 2020. To examine the implication for transmission dynamics of these correlations, we proposed a novel model, which embeds the function of individual behaviour change (media impact) into the intensity of infection. The nonlinear least squares estimation is used to identify the best-fit parameter values in the model from the observed data. To determine impact of key parameters with media impact and control measures for the later outcome of the outbreak, we also carried out the uncertainty and sensitivity analyses. These findings confirm the importance of the responses of individuals to the media reports, and the crucial role of experts and governments in promoting the public under self-quarantine. Therefore, for mitigating epidemic COVID-19, the media publicity should be focused on how to guide people’s behavioral changes by experts, and the management departments and designated hospitals of the COVID-19 should take effective quarantined measures, which are critical for the control of the disease.
has issue date	2020-06-25(xsd:dateTime)
bibo:doi	10.1016/j.jtbi.2020.110385
bibo:pmid	32593679
has license	no-cc
sha1sum (hex)	e0870a29e3968f2bc9a247c6bf29a9b536403968
schema:url	https://doi.org/10.1016/j.jtbi.2020.110385
resource representing a document's title	Impact of media reports on the early spread of COVID-19 epidemic
has PubMed Central identifier	PMC7316072
has PubMed identifier	32593679
schema:publication	J Theor Biol
resource representing a document's body	covid:e0870a29e3968f2bc9a247c6bf29a9b536403968#body_text
is http://vocab.deri.ie/void#inDataset of	proxy:http/ns.inria.fr/covid19/e0870a29e3968f2bc9a247c6bf29a9b536403968
is schema:about of	named entity 'impact' named entity 'disease' named entity 'cross-correlation' named entity 'statistically' named entity 'COVID-19' named entity 'sensitivity analyses' named entity 'measures' named entity 'changing' named entity 'responses' named entity 'Impact' named entity 'observed' named entity 'January' named entity 'epidemic' named entity 'model' named entity 'epidemic' named entity 'China' named entity 'modify' named entity 'number' named entity 'However' named entity 'attitudes' named entity 'COVID-19' named entity 'COVID-19' named entity 'Pearson correlation' named entity 'major websites' named entity 'behaviour change' named entity 'embeds' named entity 'epidemic' named entity 'Wuhan' named entity 'COVID-19 infection' named entity 'Hubei' named entity 'Cross-correlation' named entity 'contact tracing' named entity 'Wuhan' named entity 'Shandong' named entity 'exponential growth' named entity 'model selection' named entity 'China' named entity 'Hubei' named entity 'Shaanxi' named entity 'sina.com' named entity 'sina.com' named entity 'epidemic' named entity 'cross-correlation' named entity 'cross-correlation' named entity 'Pearson correlation' named entity 'cnr.cn' named entity 'epidemic' named entity 'COVID-19' named entity 'Ningxia' named entity 'COVID-19' named entity 'COVID-19' named entity '0.01' named entity 'contact tracing' named entity 'epidemic' named entity 'Hebei' named entity 'Matlab' named entity 'COVID-19' named entity 'Hubei' named entity 'provincial municipalities' named entity 'virus' named entity 'incubation period' named entity 'Cross-correlation' named entity 'China' named entity 'sina.com' named entity 'quarantine' named entity '0.01' named entity 'qq.com'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software