Early in the pandemic, individuals in numerous countries experienced quite different rates of COVID-19 infections and deaths dependent on where they lived. This within-country variation offers an opportunity to study how the intensity of a catastrophic shock to systems affects individuals' economic preferences – a topic without consensus in the literature. In April 2020, we conducted an online survey with approximately 1500 subjects in China, 800 in Chile, and 800 in Italy. Our sampling strategy deliberately sampled subjects with exposure to different levels of local COVID-19 infections. We find that respondents condition their behavior and economic preferences on this intensity – levels of COVID-19 preventive behavior are correlated with the intensity of community infections; exposure to intense infection rates correlates, positively, with risk aversion and patience; and, negatively, with other-regarding preferences. Using machine-learning to estimate individual-level effects, we find notable effect heterogeneity with respect to education levels. Finally, using multilevel regression and poststratification (MRP) we demonstrate province-level estimates of economic preferences for 107 Italian provinces.