Evidence from internet search data shows information-seeking responses to news of local COVID-19 cases.


Journal

Proceedings of the National Academy of Sciences of the United States of America
ISSN: 1091-6490
Titre abrégé: Proc Natl Acad Sci U S A
Pays: United States
ID NLM: 7505876

Informations de publication

Date de publication:
26 05 2020
Historique:
pubmed: 6 5 2020
medline: 30 5 2020
entrez: 6 5 2020
Statut: ppublish

Résumé

The COVID-19 outbreak is a global pandemic with community circulation in many countries, including the United States, with confirmed cases in all states. The course of this pandemic will be shaped by how governments enact timely policies and disseminate information and by how the public reacts to policies and information. Here, we examine information-seeking responses to the first COVID-19 case public announcement in a state. Using an event study framework for all US states, we show that such news increases collective attention to the crisis right away. However, the elevated level of attention is short-lived, even though the initial announcements are followed by increasingly strong policy measures. Specifically, searches for "coronavirus" increased by about 36% (95% CI: 27 to 44%) on the day immediately after the first case announcement but decreased back to the baseline level in less than a week or two. We find that people respond to the first report of COVID-19 in their state by immediately seeking information about COVID-19, as measured by searches for coronavirus, coronavirus symptoms, and hand sanitizer. On the other hand, searches for information regarding community-level policies (e.g., quarantine, school closures, testing) or personal health strategies (e.g., masks, grocery delivery, over-the-counter medications) do not appear to be immediately triggered by first reports. These results are representative of the study period being relatively early in the epidemic, and more-elaborate policy responses were not yet part of the public discourse. Further analysis should track evolving patterns of responses to subsequent flows of public information.

Identifiants

pubmed: 32366658
pii: 2005335117
doi: 10.1073/pnas.2005335117
pmc: PMC7260988
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

11220-11222

Informations de copyright

Copyright © 2020 the Author(s). Published by PNAS.

Déclaration de conflit d'intérêts

The authors declare no competing interest.

Références

Lancet Infect Dis. 2020 May;20(5):533-534
pubmed: 32087114
Annu Rev Public Health. 2018 Apr 1;39:453-469
pubmed: 29328877
Proc Natl Acad Sci U S A. 2007 May 1;104(18):7582-7
pubmed: 17416679
Science. 2014 Mar 14;343(6176):1203-5
pubmed: 24626916
Bull Math Biol. 2020 Apr 8;82(4):52
pubmed: 32270376
Science. 2020 Apr 24;368(6489):395-400
pubmed: 32144116

Auteurs

Ana I Bento (AI)

School of Public Health, Indiana University, Bloomington, IN 47405; abento@iu.edu simonkos@iu.edu.

Thuy Nguyen (T)

O'Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN 47405.

Coady Wing (C)

O'Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN 47405.

Felipe Lozano-Rojas (F)

O'Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN 47405.

Yong-Yeol Ahn (YY)

Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN 47408.

Kosali Simon (K)

O'Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN 47405; abento@iu.edu simonkos@iu.edu.

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Classifications MeSH