Literature DB >> 33742054

Exploring the use of web searches for risk communication during COVID-19 in Germany.

Kaja Kristensen1, Eva Lorenz2, Jürgen May2, Ricardo Strauss3.   

Abstract

Risk communication during pandemics is an element of utmost importance. Understanding the level of public attention-a prerequisite for effective communication-implicates expensive and time-consuming surveys. We hypothesise that the relative search volume from Google Trends could be used as an indicator of public attention of a disease and its prevention measures. The search terms 'RKI' (Robert Koch Institute, national public health authority in Germany), 'corona' and 'protective mask' in German language were shortlisted. Cross-correlations between these terms and the reported cases from 15 February to 27 April were conducted for each German federal state. The findings were contrasted against a timeline of official communications concerning COVID-19. The highest correlations of the term 'RKI' with reported COVID-19 cases were found between lags of - 2 and - 12 days, meaning web searches were already performed from 2 to 12 days before case numbers increased. A similar pattern was seen for the term 'corona'. Cross-correlations indicated that most searches on 'protective mask' were performed from 6 to 12 days after the peak of cases. The results for the term 'protective mask' indicate a degree of confusion in the population. This is supported by conflicting recommendations to wear face masks during the first wave. The relative search volumes could be a useful tool to provide timely and location-specific information on public attention for risk communication.

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Mesh:

Year:  2021        PMID: 33742054      PMCID: PMC7979881          DOI: 10.1038/s41598-021-85873-4

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  29 in total

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4.  A novel evaluation of World No Tobacco day in Latin America.

Authors:  John W Ayers; Benjamin M Althouse; Jon-Patrick Allem; Daniel E Ford; Kurt M Ribisl; Joanna E Cohen
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5.  Using internet search queries for infectious disease surveillance: screening diseases for suitability.

Authors:  Gabriel J Milinovich; Simon M R Avril; Archie C A Clements; John S Brownstein; Shilu Tong; Wenbiao Hu
Journal:  BMC Infect Dis       Date:  2014-12-31       Impact factor: 3.090

6.  COVID-19 predictability in the United States using Google Trends time series.

Authors:  Amaryllis Mavragani; Konstantinos Gkillas
Journal:  Sci Rep       Date:  2020-11-26       Impact factor: 4.379

7.  Public response to community mitigation measures for pandemic influenza.

Authors:  Robert J Blendon; Lisa M Koonin; John M Benson; Martin S Cetron; William E Pollard; Elizabeth W Mitchell; Kathleen J Weldon; Melissa J Herrmann
Journal:  Emerg Infect Dis       Date:  2008-05       Impact factor: 6.883

8.  Search query data to monitor interest in behavior change: application for public health.

Authors:  Lucas J Carr; Shira I Dunsiger
Journal:  PLoS One       Date:  2012-10-23       Impact factor: 3.240

9.  Applications of Google Search Trends for risk communication in infectious disease management: A case study of the COVID-19 outbreak in Taiwan.

Authors:  Atina Husnayain; Anis Fuad; Emily Chia-Yu Su
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  2 in total

1.  From science to politics: COVID-19 information fatigue on YouTube.

Authors:  Chyun-Fung Shi; Matthew C So; Sophie Stelmach; Arielle Earn; David J D Earn; Jonathan Dushoff
Journal:  BMC Public Health       Date:  2022-04-23       Impact factor: 4.135

Review 2.  Forecasting and Surveillance of COVID-19 Spread Using Google Trends: Literature Review.

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  2 in total

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