Social Interactions in Pandemics: Fear, Altruism, and Reciprocity

Social interactions and social preferences play a central role in public health domains. In the face of a pandemic, individuals adjust their behavior, whereas in SIR models infection rates are typically exogenous. City-level data across countries suggest that mobility falls in response to fear, proxied by Google searches. Incorporating experimentally validated measures of social preferences at the regional level, we find that stringency measures matter less when individuals are more patient, altruistic, or exhibit less negative reciprocity. To account for these findings, we extend homogeneous and networked SIR models by endogenizing agents' social-activity intensity and incorporating social preferences. Our quantitative predictions markedly differ from those of the naïve SIR network model. We derive the planner's problem, and show that neglecting agents' endogenous response leads to misguided policy decisions of various non-pharmaceutical interventions. Any further mobility restrictions, beyond agents' restraint, result from aggregate externalities which are curtailed by social preferences.