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Google Trends Data and COVID-19 in Europe: correlations and model enhancement are European wide
  • Mihály Sulyok,
  • Mark Walker
Mihály Sulyok
Eberhard Karls University Tübingen

Corresponding Author:sulyok.mihaly@gmail.com

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Mark Walker
Sheffield Hallam University Department of the Natural and Built Environment
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Abstract

The current COVID-19 pandemic offers a unique opportunity to examine the utility of Internet search data in disease modelling across multiple countries. Google Trends data (GTD) indicating the volume of Internet searching on ‘Coronavirus’ were obtained for a range of European countries along with corresponding incident case numbers. Significant positive correlations between GTD with incident case numbers occurred across European countries, with the strongest correlations being obtained using contemporaneous data for most countries. GTD was then integrated into a lag distributed model; this improved model quality for both the increasing and decreasing epidemic phases.
05 Aug 2020Submitted to Transboundary and Emerging Diseases
06 Aug 2020Submission Checks Completed
06 Aug 2020Assigned to Editor
09 Aug 2020Reviewer(s) Assigned
17 Sep 2020Review(s) Completed, Editorial Evaluation Pending
19 Sep 2020Editorial Decision: Revise Major
30 Sep 20201st Revision Received
01 Oct 2020Submission Checks Completed
01 Oct 2020Assigned to Editor
02 Oct 2020Reviewer(s) Assigned
18 Oct 2020Review(s) Completed, Editorial Evaluation Pending
18 Oct 2020Editorial Decision: Accept
17 Nov 2020Published in Transboundary and Emerging Diseases. 10.1111/tbed.13887