Tracking COVID-19 in Europe: Infodemiology Approach.
Identifieur interne : 000340 ( Main/Exploration ); précédent : 000339; suivant : 000341Tracking COVID-19 in Europe: Infodemiology Approach.
Auteurs : Amaryllis Mavragani [Royaume-Uni]Source :
- JMIR public health and surveillance [ 2369-2960 ] ; 2020.
Descripteurs français
- KwdFr :
- MESH :
- méthodes : Surveillance de la santé publique.
- tendances : Moteur de recherche.
- épidémiologie : Europe, Infections à coronavirus, Pneumopathie virale.
- Humains, Internet, Mémorisation et recherche des informations, Pandémies.
English descriptors
- KwdEn :
- MESH :
- geographic , epidemiology : Europe.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- methods : Public Health Surveillance.
- trends : Search Engine.
- Humans, Information Storage and Retrieval, Internet, Pandemics.
Abstract
BACKGROUND
Infodemiology (ie, information epidemiology) uses web-based data to inform public health and policy. Infodemiology metrics have been widely and successfully used to assess and forecast epidemics and outbreaks.
OBJECTIVE
In light of the recent coronavirus disease (COVID-19) pandemic that started in Wuhan, China in 2019, online search traffic data from Google are used to track the spread of the new coronavirus disease in Europe.
METHODS
Time series from Google Trends from January to March 2020 on the Topic (Virus) of "Coronavirus" were retrieved and correlated with official data on COVID-19 cases and deaths worldwide and in the European countries that have been affected the most: Italy (at national and regional level), Spain, France, Germany, and the United Kingdom.
RESULTS
Statistically significant correlations are observed between online interest and COVID-19 cases and deaths. Furthermore, a critical point, after which the Pearson correlation coefficient starts declining (even if it is still statistically significant) was identified, indicating that this method is most efficient in regions or countries that have not yet peaked in COVID-19 cases.
CONCLUSIONS
In the past, infodemiology metrics in general and data from Google Trends in particular have been shown to be useful in tracking and forecasting outbreaks, epidemics, and pandemics as, for example, in the cases of the Middle East respiratory syndrome, Ebola, measles, and Zika. With the COVID-19 pandemic still in the beginning stages, it is essential to explore and combine new methods of disease surveillance to assist with the preparedness of health care systems at the regional level.
DOI: 10.2196/18941
PubMed: 32250957
PubMed Central: PMC7173241
Affiliations:
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Infodemiology metrics have been widely and successfully used to assess and forecast epidemics and outbreaks.</p></div><div type="abstract" xml:lang="en"><p><b>OBJECTIVE</b></p><p>In light of the recent coronavirus disease (COVID-19) pandemic that started in Wuhan, China in 2019, online search traffic data from Google are used to track the spread of the new coronavirus disease in Europe.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>Time series from Google Trends from January to March 2020 on the Topic (Virus) of "Coronavirus" were retrieved and correlated with official data on COVID-19 cases and deaths worldwide and in the European countries that have been affected the most: Italy (at national and regional level), Spain, France, Germany, and the United Kingdom.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>Statistically significant correlations are observed between online interest and COVID-19 cases and deaths. Furthermore, a critical point, after which the Pearson correlation coefficient starts declining (even if it is still statistically significant) was identified, indicating that this method is most efficient in regions or countries that have not yet peaked in COVID-19 cases.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>In the past, infodemiology metrics in general and data from Google Trends in particular have been shown to be useful in tracking and forecasting outbreaks, epidemics, and pandemics as, for example, in the cases of the Middle East respiratory syndrome, Ebola, measles, and Zika. With the COVID-19 pandemic still in the beginning stages, it is essential to explore and combine new methods of disease surveillance to assist with the preparedness of health care systems at the regional level.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32250957</PMID><DateCompleted><Year>2020</Year><Month>04</Month><Day>24</Day></DateCompleted><DateRevised><Year>2020</Year><Month>04</Month><Day>24</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">2369-2960</ISSN><JournalIssue CitedMedium="Internet"><Volume>6</Volume><Issue>2</Issue><PubDate><Year>2020</Year><Month>04</Month><Day>20</Day></PubDate></JournalIssue><Title>JMIR public health and surveillance</Title><ISOAbbreviation>JMIR Public Health Surveill</ISOAbbreviation></Journal><ArticleTitle>Tracking COVID-19 in Europe: Infodemiology Approach.</ArticleTitle><Pagination><MedlinePgn>e18941</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.2196/18941</ELocationID><Abstract><AbstractText Label="BACKGROUND">Infodemiology (ie, information epidemiology) uses web-based data to inform public health and policy. Infodemiology metrics have been widely and successfully used to assess and forecast epidemics and outbreaks.</AbstractText><AbstractText Label="OBJECTIVE">In light of the recent coronavirus disease (COVID-19) pandemic that started in Wuhan, China in 2019, online search traffic data from Google are used to track the spread of the new coronavirus disease in Europe.</AbstractText><AbstractText Label="METHODS">Time series from Google Trends from January to March 2020 on the Topic (Virus) of "Coronavirus" were retrieved and correlated with official data on COVID-19 cases and deaths worldwide and in the European countries that have been affected the most: Italy (at national and regional level), Spain, France, Germany, and the United Kingdom.</AbstractText><AbstractText Label="RESULTS">Statistically significant correlations are observed between online interest and COVID-19 cases and deaths. Furthermore, a critical point, after which the Pearson correlation coefficient starts declining (even if it is still statistically significant) was identified, indicating that this method is most efficient in regions or countries that have not yet peaked in COVID-19 cases.</AbstractText><AbstractText Label="CONCLUSIONS">In the past, infodemiology metrics in general and data from Google Trends in particular have been shown to be useful in tracking and forecasting outbreaks, epidemics, and pandemics as, for example, in the cases of the Middle East respiratory syndrome, Ebola, measles, and Zika. With the COVID-19 pandemic still in the beginning stages, it is essential to explore and combine new methods of disease surveillance to assist with the preparedness of health care systems at the regional level.</AbstractText><CopyrightInformation>©Amaryllis Mavragani. 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