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

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 expose

SUBMITTER: Romano A 

PROVIDER: S-EPMC7461444 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature