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Cited by 214

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COVID-19: Reflections on trust, tradeoffs, and preparedness

Balog-Way, Dominic H. P., McComas, Katherine A.·2020·Journal of Risk Research

Abstract

The global coronavirus disease (COVID-19) pandemic has already had an enormous impact and will surely have profound consequences for many years to come. The authors reflect on three risk communication themes related to the pandemic: trust, tradeoffs, and preparedness. Trust is critically important during such a rapidly evolving event characterized by scientific uncertainty. Reflections focus on uncertainty communication, transparency, and long-term implications for trust in government and science. On tradeoffs, the positive and unintended negative effects of three key risk communication messages are considered (1) stay at home, (2) some groups are at higher risk, and (3) daily infections and deaths. The authors argue that greater attention to message ‘tradeoffs’ over ‘effectiveness’ and ‘evaluation’ over ‘intuition’ would help guide risk communicators under pressure. On preparedness, past infectious disease outbreak recommendations are examined. Although COVID-19 was inevitably ‘unexpected’, important preparedness actions were largely overlooked such as building key risk communication capacities.

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Metadata

Authors
Balog-Way, D. H. P., & McComas, K. A.
Venue
Journal of Risk Research
Published
2020-04-27
Volume
23
Issue
7-8
Pages
838-848
ISSN
  • 1366-9877 (ISSN-L)
  • 1466-4461
OpenAlex
W3020481122
Cited by
214
References
0
FWCI
53.39
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: COVID-19: Reflections on trust, tradeoffs, and preparedness. https://app.cochat.ai/papers/10.1080/13669877.2020.1758192
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Balog-Way, D. H. P., & McComas, K. A. (2020). COVID-19: Reflections on trust, tradeoffs, and preparedness. Journal of Risk Research. https://doi.org/10.1080/13669877.2020.1758192

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.