Higher-order adaptive behaviors outperform pairwise strategies in mitigating contagion dynamics

2026-02-05

AI Summary

This study investigates how risk-perception-driven adaptive behaviors—mediated through higher-order (group) and pairwise interactions—can suppress epidemic spreading and reduce social costs. By modeling the population contact structure as a hypergraph and combining numerical simulations with mean-field theory, this work presents the first systematic comparison of the effectiveness between these two classes of adaptive strategies. The findings demonstrate that higher-order adaptive strategies substantially outperform pairwise ones: they not only more effectively curb transmission but also achieve greater precision in mitigating the dominant role of high-degree nodes and large groups in disease spread, all at a lower social cost. These results highlight the critical value of heterogeneity in risk perception—induced by higher-order information—for enabling targeted and efficient public health interventions.

Technology Category

• Game Theory and Economic Paradigms: Adversarial Learning
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Search and Optimization: Metareasoning and Metaheuristics

Application Category

• Economics, Online Markets and Human Computation: Social networks and social learning
• Social Networks and Social Media: Influence propagation, information diffusion, and the prediction on networks
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

When exposed to a contagion phenomenon, individuals may respond to the perceived risk of infection by adopting behavioral changes, aiming to reduce their exposure or their risk of infecting others. The social cost of such adaptive behaviors and their impact on the contagion dynamics have been investigated in pairwise networks, with binary interactions driving both contagion and risk perception. However, contagion and adaptive mechanisms can also be driven by group (higher-order) interactions. Here, we consider several adaptive behaviors triggered by awareness of risk perceived through higher-order and pairwise interactions, and we compare their impact on pairwise and higher-order contagion processes. By numerical simulations and a mean-field analytic approach, we show that adaptive behaviors driven by higher-order information are more effective in limiting the spread of a contagion, than similar mechanisms based on pairwise information. Meanwhile, they also entail a lower social cost, measured as the reduction of the intensity of interactions in the population. Indeed, adaptive mechanisms based on higher-order information lead to a heterogeneous risk perception within the population, producing a higher alert on nodes with large hyperdegree (i.e., participating in many groups), on their neighborhoods, and on large groups. This in turn prevents the spreading process to exploit the properties of these nodes and groups, which tend to drive and sustain the dynamics in the absence of adaptive behaviors.

Problem

• contagion dynamics
• adaptive behavior
• higher-order interactions
• risk perception
• social cost

Innovation

• higher-order interactions
• adaptive behavior
• contagion dynamics
• risk perception
• hyperdegree