ABSTRACT From how public opinion responds to economic outcomes to how risk perception shapes social interactions during a pandemic, many important social processes involve the assimilation of information to form opinions and perceptions, which in turn guide individual and societal actions. While such perception delays are well recognized, empirically identifying them is nontrivial. We study this problem in the context of human responses to disease dynamics, mediated by public risk perception. Public risk perception changes through an information diffusion process with significant delays, where perception adjustment delay may differ depending on whether the risk is increasing or decreasing. Despite these complexities, most models assume either fixed‐delay structures or exponential structures with symmetric delay periods. First, using synthetic data (where ground truth is known), we show that incorrect delay structures and the assumption of symmetric delay periods can lead to biased and misleading estimates. We then explore alternative approaches to identify more appropriate delay structures that can overcome these challenges. Second, we apply these asymmetric delay structures to state‐level US COVID‐19 disease and mobility data to demonstrate how estimates of public sensitivity to mortality depend on the assumed delay structure. Our results provide evidence that during the pandemic, human risk perception adjusted with asymmetric delays to changing risk: people perceived rising risks more quickly than they perceived declining risks.
Shalmani et al. (Mon,) studied this question.