During the coronavirus disease 2019 (COVID-19) pandemic, data regarding new infections were commonly presented and used to guide policy decisions (e.g., whether to close schools) and personal choices (e.g., whether to dine at a restaurant). In this manuscript, we highlight a critical aspect of pandemic data that can pose a challenge for people trying to reason about it. Data on infections-like much time series data-can be presented as either stocks (the total number of cases) or flows (the number of new cases over some interval). We show that seeing the same data presented in one format versus the other can shift judgments of risk and behavioral intentions. Specifically, when participants were shown data that depicted the number of new cases each day (flow) decreasing, they judged the current risk of COVID-19 to be lower than participants who were shown the same data as the total (cumulative) number of cases (stock), which-by its nature-continued to increase. Risk appraisal, in turn, predicted a wide array of behavioral intentions (e.g., likelihood of dining indoors at a restaurant). Thus, the choice of how to present pandemic data can lead people to different conclusions about risk and can have practical consequences for risky behavior. (PsycInfo Database Record (c) 2022 APA, all rights reserved).