The Complex Interplay Between Risk Tolerance and the Spread of Infectious Diseases

TL;DR

This paper introduces a flexible model to study how individual risk tolerance heterogeneity influences epidemic dynamics, revealing complex behaviors like multiple waves and non-monotonic epidemic size responses to behavioral changes.

Contribution

It presents a novel compartmental model capturing risk tolerance heterogeneity and its impact on epidemic outcomes, including multiple waves and thresholds for intervention effectiveness.

Findings

Heterogeneity in risk tolerance can both increase or decrease epidemic size.

Multiple infection waves can occur without susceptible replenishment.

Interventions can reduce epidemic overshoot and lead to herd immunity.

Abstract

Risk-driven behavior provides a feedback mechanism through which individuals both shape and are collectively affected by an epidemic. We introduce a general and flexible compartmental model to study the effect of heterogeneity in the population with regards to risk tolerance. The interplay between behavior and epidemiology leads to a rich set of possible epidemic dynamics. Depending on the behavioral composition of the population, we find that increasing heterogeneity in risk tolerance can either increase or decrease the epidemic size. We find that multiple waves of infection can arise due to the interplay between transmission and behavior, even without the replenishment of susceptibles. We find that increasing protective mechanisms such as the effectiveness of interventions, the number of risk-averse people in the population, and the duration of intervention usage reduces the epidemic overshoot. When the protection is pushed past a critical threshold, the epidemic dynamics enter an underdamped regime where the epidemic size exactly equals the herd immunity threshold. Lastly, we can find regimes where epidemic size does not monotonically decrease with a population that becomes increasingly risk-averse.