SSOAR Logo
    • Deutsch
    • English
  • English 
    • Deutsch
    • English
  • Login
SSOAR ▼
  • Home
  • About SSOAR
  • Guidelines
  • Publishing in SSOAR
  • Cooperating with SSOAR
    • Cooperation models
    • Delivery routes and formats
    • Projects
  • Cooperation partners
    • Information about cooperation partners
  • Information
    • Possibilities of taking the Green Road
    • Grant of Licences
    • Download additional information
  • Operational concept
Browse and search Add new document OAI-PMH interface
JavaScript is disabled for your browser. Some features of this site may not work without it.

Download PDF
Download full text

(6.230Mb)

Citation Suggestion

Please use the following Persistent Identifier (PID) to cite this document:
https://nbn-resolving.org/urn:nbn:de:0168-ssoar-78933-8

Exports for your reference manager

Bibtex export
Endnote export

Display Statistics
Share
  • Share via E-Mail E-Mail
  • Share via Facebook Facebook
  • Share via Bluesky Bluesky
  • Share via Reddit reddit
  • Share via Linkedin LinkedIn
  • Share via XING XING

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

[journal article]

Kristensen, Kaja
Lorenz, Eva
May, Jürgen
Strauss, Ricardo

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 in... view more

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.... view less

Keywords
Federal Republic of Germany; epidemic; risk communication; search engine; digital media; trend; prophylaxis; illness; information-seeking behavior

Classification
Health Policy
Interactive, electronic Media

Free Keywords
COVID-19; Coronavirus; Google; GESIS Panel Special Survey on the Coronavirus SARS-CoV-2 Outbreak in Germany (ZA5667 v1.1.0)

Document language
English

Publication Year
2021

Page/Pages
p. 1-10

Journal
Scientific Reports, 11 (2021)

DOI
https://doi.org/10.1038/s41598-021-85873-4

ISSN
2045-2322

Status
Published Version; peer reviewed

Licence
Creative Commons - Attribution 4.0


GESIS LogoDFG LogoOpen Access Logo
Home  |  Legal notices  |  Operational concept  |  Privacy policy
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.
 

 


GESIS LogoDFG LogoOpen Access Logo
Home  |  Legal notices  |  Operational concept  |  Privacy policy
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.