| Abstract: |
| Mathematical models of infectious disease transmission increasingly support public health decision-making, yet observed epidemic dynamics reflect not only pathogen biology but also adaptive human behavior. Behavioral responses to perceived risk can alter contact patterns and transmission. When such feedbacks are ignored or absorbed into constant parameters, models may reproduce epidemic trajectories while implying unrealistic outbreak sizes. In this talk, we revisit the well-known 1978 influenza outbreak in a British boys boarding school. Standard SIR models fitted to the infection time series typically fail to explain the large fraction of students who remained uninfected. We show that this discrepancy reflects a structural limitation of constant-transmission models rather than a parameter estimation issue. We then infer a time-varying transmission rate and introduce perceived prevalence, a short-term memory of recent infections that approximates how severe the outbreak appears to the population. Incorporating this behavioral driver allows a minimal SIR model to match both the infection time course and the final outbreak size. We then translate these inferred dynamics into an agent-based model to examine whether the behavioral response reflects reduced contact rates or changes in per-contact transmission probability, while allowing heterogeneity in susceptibility through innate immunity among the students. |
|