Game-theoretic modeling of collective decision-making during epidemics

Abstract

The spreading dynamics of an epidemic and the collective behavioral pattern of the population over which it spreads are deeply intertwined and the latter can critically shape the outcome of the former. Motivated by this, we design a parsimonious game-theoretic behavioral--epidemic model, in which an interplay of realistic factors shapes the co-evolution of individual decision-making and epidemics on a network. Although such a co-evolution is deeply intertwined in the real-world, existing models schematize population behavior as instantaneously reactive, thus being unable to capture human behavior in the long term. Our model offers a unified framework to model and predict complex emergent phenomena, including successful collective responses, periodic oscillations, and resurgent epidemic outbreaks. The framework also allows to assess the effectiveness of different policy interventions on ensuring a collective response that successfully eradicates the outbreak. Two case studies, inspired by real-world diseases, are presented to illustrate the potentialities of the proposed model.

Under Review

References in corpus (6)

• The structure and dynamics of multilayer networks
• Activity driven modeling of time varying networks
• Non-pharmaceutical interventions during the COVID-19 pandemic: a rapid review
• Towards a characterization of behavior-disease models
• Analytical computation of the epidemic threshold on temporal networks
• Self-initiated behavioural change and disease resurgence on activity-driven networks

Cited by in corpus (10)

• Information Dynamics in Evolving Networks Based on the Birth-Death Process: Random Drift and Natural Selection Perspective
• A mean-field analysis of a network behavioural-epidemic model
• Epidemic spreading under game-based self-quarantine behaviors: The different effects of local and global information
• A geometric analysis of the SIRS compartmental model with fast information and misinformation spreading
• Coupled dynamics of endemic disease transmission and gradual awareness diffusion in multiplex networks
• Data-informed modeling of the formation, persistence, and evolution of social norms and conventions
• A Human-Vector Susceptible-Infected-Susceptible Model for Analyzing and Controlling the Spread of Vector-Borne Diseases
• Recent trends in socio-epidemic modelling: behaviours and their determinants
• A Quantum Approach for Optimal Transient Control in Network-Based Epidemic Models
• Evolutionary dynamics of collective decision-making with local social influence on static and dynamic networks