CovidV2, PubMed, Checkpoint, bibRecord, 000362

Retrospective analysis of the possibility of predicting the COVID-19 outbreak from Internet searches and social media data, China, 2020.

Identifieur interne : 000362 ( PubMed/Checkpoint ); précédent : 000361; suivant : 000363

Retrospective analysis of the possibility of predicting the COVID-19 outbreak from Internet searches and social media data, China, 2020.

Auteurs : Cuilian Li [République populaire de Chine] ; Li Jia Chen [République populaire de Chine] ; Xueyu Chen [République populaire de Chine] ; Mingzhi Zhang [République populaire de Chine] ; Chi Pui Pang [République populaire de Chine] ; Haoyu Chen [République populaire de Chine]

Source :

Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin [ 1560-7917 ] ; 2020.

RBID : pubmed:32183935

Descripteurs français

KwdFr :
- Chine (épidémiologie), Flambées de maladies (), Humains, Incidence, Infections à coronavirus (diagnostic), Infections à coronavirus (transmission), Infections à coronavirus (épidémiologie), Internet, Laboratoires (), Moteur de recherche (), Médias sociaux (), Médias sociaux (tendances), Navigateur (), Navigateur (tendances), Pneumopathie virale (diagnostic), Pneumopathie virale (transmission), Pneumopathie virale (épidémiologie), Pratique en santé publique, Surveillance de la population ().
MESH :
- diagnostic : Infections à coronavirus, Pneumopathie virale.
- tendances : Médias sociaux, Navigateur.
- épidémiologie : Chine, Infections à coronavirus, Pneumopathie virale.
- Flambées de maladies, Humains, Incidence, Internet, Laboratoires, Moteur de recherche, Médias sociaux, Navigateur, Pratique en santé publique, Surveillance de la population.
Wicri :
- geographic : République populaire de Chine.

English descriptors

KwdEn :
- China (epidemiology), Coronavirus Infections (diagnosis), Coronavirus Infections (epidemiology), Coronavirus Infections (transmission), Disease Outbreaks (statistics & numerical data), Humans, Incidence, Internet, Laboratories (statistics & numerical data), Pneumonia, Viral (diagnosis), Pneumonia, Viral (epidemiology), Pneumonia, Viral (transmission), Population Surveillance (methods), Public Health Practice, Search Engine (statistics & numerical data), Social Media (statistics & numerical data), Social Media (trends), Web Browser (statistics & numerical data), Web Browser (trends).
MESH :
- geographic , epidemiology : China.
- diagnosis : Coronavirus Infections, Pneumonia, Viral.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- methods : Population Surveillance.
- statistics & numerical data : Disease Outbreaks, Laboratories, Search Engine, Social Media, Web Browser.
- transmission : Coronavirus Infections, Pneumonia, Viral.
- trends : Social Media, Web Browser.
- Humans, Incidence, Internet, Public Health Practice.

Abstract

The peak of Internet searches and social media data about the coronavirus disease 2019 (COVID-19) outbreak occurred 10-14 days earlier than the peak of daily incidences in China. Internet searches and social media data had high correlation with daily incidences, with the maximum r > 0.89 in all correlations. The lag correlations also showed a maximum correlation at 8-12 days for laboratory-confirmed cases and 6-8 days for suspected cases.

DOI: 10.2807/1560-7917.ES.2020.25.10.2000199
PubMed: 32183935

Affiliations:

Links toward previous steps (curation, corpus...)

to stream PubMed, to step Corpus: 000381
to stream PubMed, to step Curation: 000381

Links to Exploration step

pubmed:32183935

Le document en format XML

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<front><div type="abstract" xml:lang="en">The peak of Internet searches and social media data about the coronavirus disease 2019 (COVID-19) outbreak occurred 10-14 days earlier than the peak of daily incidences in China. Internet searches and social media data had high correlation with daily incidences, with the maximum r > 0.89 in all correlations. The lag correlations also showed a maximum correlation at 8-12 days for laboratory-confirmed cases and 6-8 days for suspected cases.</div>
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<Abstract><AbstractText>The peak of Internet searches and social media data about the coronavirus disease 2019 (COVID-19) outbreak occurred 10-14 days earlier than the peak of daily incidences in China. Internet searches and social media data had high correlation with daily incidences, with the maximum r > 0.89 in all correlations. The lag correlations also showed a maximum correlation at 8-12 days for laboratory-confirmed cases and 6-8 days for suspected cases.</AbstractText>
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<ArticleIdList><ArticleId IdType="pubmed">19941777</ArticleId>
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</PubmedData>
</pubmed>
<affiliations><list><country><li>République populaire de Chine</li>
</country>
<settlement><li>Sha Tin</li>
</settlement>
<orgName><li>Université chinoise de Hong Kong</li>
</orgName>
</list>
<tree><country name="République populaire de Chine"><noRegion><name sortKey="Li, Cuilian" sort="Li, Cuilian" uniqKey="Li C" first="Cuilian" last="Li">Cuilian Li</name>
</noRegion>
<name sortKey="Chen, Haoyu" sort="Chen, Haoyu" uniqKey="Chen H" first="Haoyu" last="Chen">Haoyu Chen</name>
<name sortKey="Chen, Li Jia" sort="Chen, Li Jia" uniqKey="Chen L" first="Li Jia" last="Chen">Li Jia Chen</name>
<name sortKey="Chen, Xueyu" sort="Chen, Xueyu" uniqKey="Chen X" first="Xueyu" last="Chen">Xueyu Chen</name>
<name sortKey="Pang, Chi Pui" sort="Pang, Chi Pui" uniqKey="Pang C" first="Chi Pui" last="Pang">Chi Pui Pang</name>
<name sortKey="Zhang, Mingzhi" sort="Zhang, Mingzhi" uniqKey="Zhang M" first="Mingzhi" last="Zhang">Mingzhi Zhang</name>
</country>
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Retrospective analysis of the possibility of predicting the COVID-19 outbreak from Internet searches and social media data, China, 2020.

Retrospective analysis of the possibility of predicting the COVID-19 outbreak from Internet searches and social media data, China, 2020.

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