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Tracking COVID-19 in Europe: Infodemiology Approach.
JMIR Public Health Surveill. 2020 04 20; 6(2):e18941.JP

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.

Authors+Show Affiliations

Department of Computing Science and Mathematics, Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32250957

Citation

Mavragani, Amaryllis. "Tracking COVID-19 in Europe: Infodemiology Approach." JMIR Public Health and Surveillance, vol. 6, no. 2, 2020, pp. e18941.
Mavragani A. Tracking COVID-19 in Europe: Infodemiology Approach. JMIR Public Health Surveill. 2020;6(2):e18941.
Mavragani, A. (2020). Tracking COVID-19 in Europe: Infodemiology Approach. JMIR Public Health and Surveillance, 6(2), e18941. https://doi.org/10.2196/18941
Mavragani A. Tracking COVID-19 in Europe: Infodemiology Approach. JMIR Public Health Surveill. 2020 04 20;6(2):e18941. PubMed PMID: 32250957.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Tracking COVID-19 in Europe: Infodemiology Approach. A1 - Mavragani,Amaryllis, Y1 - 2020/04/20/ PY - 2020/03/28/received PY - 2020/04/02/accepted PY - 2020/4/7/pubmed PY - 2020/4/25/medline PY - 2020/4/7/entrez KW - COVID-19 KW - Google Trends KW - big data KW - coronavirus KW - infodemiology KW - infoveillance SP - e18941 EP - e18941 JF - JMIR public health and surveillance JO - JMIR Public Health Surveill VL - 6 IS - 2 N2 - 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. SN - 2369-2960 UR - https://www.unboundmedicine.com/medline/citation/32250957/Tracking_COVID_19_in_Europe:_Infodemiology_Approach_ L2 - https://publichealth.jmir.org/2020/2/e18941/ DB - PRIME DP - Unbound Medicine ER -