Localized risk perception triggers early behavioral adaptations in epidemics on networks

TL;DR

This study models how individual behavioral adaptations based on local risk perceptions influence epidemic progression on networks, revealing that personal responses often peak before the epidemic's maximum, affecting overall epidemic dynamics.

Contribution

It introduces a behavioral-epidemiological model capturing local risk perception-driven contact adaptations and their impact on epidemic evolution on networks.

Findings

Behavioral responses peak at epidemic maximum

Population efforts remain modest despite local adaptations

Localized risk perceptions induce premature population responses

Abstract

The contact structure of the population shapes the progression of epidemics. Nonetheless, the joint evolution of individual behavioral adaptations and disease dynamics on networks remains poorly understood. We use a behavioral-epidemiological model to study the joint evolution of human behavior and epidemic dynamics on networks. Our results reveal how the adaptation of local social structures, influenced by risk-benefit trade-offs, affects the dynamics of epidemics. We allow the epidemic and population-level behavior dynamics to emerge from the heterogeneous behavioral responses of individuals. Our framework assumes that individuals adjust their contact structure by temporarily dropping or maintaining connections based on perceived benefits and risks. Our results show that behavioral responses induced by localized risk perceptions lead to premature population-level responses relative to epidemic dynamics. Specifically, individual efforts peak at the epidemic maximum, while population-level efforts remain modest. We explore the robustness and extensions incorporating heterogeneous subpopulations.