Am I safe? A preliminary examination of how everyday people interpret covid data visualizations

During these past years, international COVID data have been collected by several reputable organizations and made available to the worldwide community. This has resulted in a wellspring of different visualizations. Many different measures can be selected (e.g., cases, deaths, hospitalizations). And for each measure, designers and policy makers can make a myriad of different choices of how to represent the data. Data from individual countries may be presented on linear or log scales, daily, weekly, or cumulative, alone or in the context of other countries, scaled to a common grid, or scaled to their own range, raw or per capita, etc. It is well known that the data representation can influence the interpretation of data. But, what visual features in these different representations affect our judgments? To explore this idea, we conducted an experiment where we asked participants to look at time-series data plots and assess how safe they would feel if they were traveling to one of the countries represented, and how confident they are of their judgment. Observers rated 48 visualizations of the same data, rendered differently along 6 controlled dimensions. Our initial results provide insight into how characteristics of the visual representation affect human judgments of time series data. We also discuss how these results could impact how public policy and news organizations choose to represent data to the public.