Speaker
Description
During the COVID-19 pandemic, individuals initially responded to epidemic risk through high-cost interventions such as mobility reduction. However, empirical data reveal that mobility reductions became less pronounced in later waves despite persistent death rates. This declining responsiveness likely reflects economic constraints, psychological fatigue, and learning about disease risk that shift individuals toward alternative cost-effective protective measures (e.g., mask wearing). Existing aggregate behavioral feedback models fail to capture this reallocation of protective behavior across interventions. In this study, we formalize this micro-level behavioral adaptation by incorporating an explicit learning mechanism, driven by accumulated pandemic experience, that shifts individuals from high-cost interventions (such as mobility reduction) toward lower-cost measures (such as mask wearing) within a risk-responsive epidemic model.
