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10.1038/s41598-021-85873-4

http://scihub22266oqcxt.onion/10.1038/s41598-021-85873-4
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33742054!7979881!33742054
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suck abstract from ncbi


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pmid33742054      Sci+Rep 2021 ; 11 (1): 6419
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  • Exploring the use of web searches for risk communication during COVID-19 in Germany #MMPMID33742054
  • Kristensen K; Lorenz E; May J; Strauss R
  • Sci Rep 2021[Mar]; 11 (1): 6419 PMID33742054show ga
  • 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.
  • |*Search Engine[MESH]
  • |COVID-19/*epidemiology/prevention & control[MESH]
  • |Communication[MESH]
  • |Germany/epidemiology[MESH]
  • |Humans[MESH]
  • |Masks[MESH]
  • |Public Health[MESH]


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