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The scale of COVID‐19 graphs affects understanding, attitudes, and policy preferences

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  • Alessandro Romano
  • Chiara Sotis
  • Goran Dominioni
  • Sebastián Guidi

Abstract

Mass media routinely present data on coronavirus disease 2019 (COVID‐19) diffusion with graphs that use either a log scale or a linear scale. We show that the choice of the scale adopted on these graphs has important consequences on how people understand and react to the information conveyed. In particular, we find that when we show the number of COVID‐19 related deaths on a logarithmic scale, people have a less accurate understanding of how the pandemic has developed, make less accurate predictions on its evolution, and have different policy preferences than when they are exposed to a linear scale. Consequently, merely changing the scale the data is presented on can alter public policy preferences and the level of worry about the pandemic, despite the fact that people are routinely exposed to COVID‐19 related information. Providing the public with information in ways they understand better can help improving the response to COVID‐19, thus, mass media and policymakers communicating to the general public should always describe the evolution of the pandemic using a graph on a linear scale, at least as a default option. Our results suggest that framing matters when communicating to the public.

Suggested Citation

  • Alessandro Romano & Chiara Sotis & Goran Dominioni & Sebastián Guidi, 2020. "The scale of COVID‐19 graphs affects understanding, attitudes, and policy preferences," Health Economics, John Wiley & Sons, Ltd., vol. 29(11), pages 1482-1494, November.
  • Handle: RePEc:wly:hlthec:v:29:y:2020:i:11:p:1482-1494
    DOI: 10.1002/hec.4143
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    References listed on IDEAS

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    1. Bursztyn, Leonardo & Rao, Akaash & Roth, Christopher & Yanagizawa-Drott, David, 2020. "Misinformation during a Pandemic," The Warwick Economics Research Paper Series (TWERPS) 1274, University of Warwick, Department of Economics.
    2. Adam Brzezinski & Valentin Kecht & David Van Dijcke & Austin L. Wright, 2020. "Belief in Science Influences Physical Distancing in Response to COVID-19 Lockdown Policies," Working Papers 2020-56, Becker Friedman Institute for Research In Economics.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Chris Sampson’s journal round-up for 2nd November 2020
      by Chris Sampson in The Academic Health Economists' Blog on 2020-11-02 12:00:08

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    2. Blayac, Thierry & Dubois, Dimitri & Duchêne, Sébastien & Nguyen-Van, Phu & Ventelou, Bruno & Willinger, Marc, 2022. "What drives the acceptability of restrictive health policies: An experimental assessment of individual preferences for anti-COVID 19 strategies," Economic Modelling, Elsevier, vol. 116(C).
    3. Chiara Sotis & Miriam Allena & Renny Reyes & Alessandro Romano, 2021. "COVID-19 Vaccine Passport and International Traveling: The Combined Effect of Two Nudges on Americans’ Support for the Pass," IJERPH, MDPI, vol. 18(16), pages 1-17, August.
    4. Lyndal J. Trevena & Carissa Bonner & Yasmina Okan & Ellen Peters & Wolfgang Gaissmaier & Paul K. J. Han & Elissa Ozanne & Danielle Timmermans & Brian J. Zikmund-Fisher, 2021. "Current Challenges When Using Numbers in Patient Decision Aids: Advanced Concepts," Medical Decision Making, , vol. 41(7), pages 834-847, October.
    5. Beate Jahn & Sarah Friedrich & Joachim Behnke & Joachim Engel & Ursula Garczarek & Ralf Münnich & Markus Pauly & Adalbert Wilhelm & Olaf Wolkenhauer & Markus Zwick & Uwe Siebert & Tim Friede, 2022. "On the role of data, statistics and decisions in a pandemic," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(3), pages 349-382, September.

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