Aug 2026· Proceedings of the National Academy of Sciences of the United States of America· Vol 123 32, pp.
e2604207123
· 0 citations· 42 references
Medicine
TL;DR
A mathematical model of two interacting groups is presented to investigate how epidemic outcomes are affected by the choice of information source, i.e., one's own group and/or the other group, resulting in a persistent infection level difference between groups that is driven by each group's choice of its information source.
Abstract
During an epidemic, disease transmission and human behavior are closely related: High infection levels trigger risk awareness and preventive behaviors, which suppress the transmission of disease. While these coupled dynamics have been heavily investigated, both in well-mixed populations and networked populations, less has been done to explore how different ways to establish the awareness of disease affect infection levels. This study presents a mathematical model of two interacting groups (populations) to investigate how epidemic outcomes are affected by the choice of information source, i.e., one's own group and/or the other group. We demonstrate that for different physical contact patterns the system can undergo a bifurcation from a uniform endemic equilibrium to a nonuniform endemic equilibrium, resulting in a persistent infection level difference between groups that is driven by each group's choice of its information source. Our results reveal strategies to minimize infection: 1) a group with low infection level benefits by prioritizing information from a group with high infection level thereby overestimating risk and 2) a group with high infection level benefits by accessing information only about its own infection level thereby avoiding underestimation of risk. These results emphasize the need to promote awareness of disease levels in addition to observation of antiepidemic measures. We highlight conditions under which strategies that benefit one group may conflict with strategies that benefit the total infection level of both groups.
The analysis identifies behavior-disease coupling through endogenous isolation as a population-level mechanism that modifies both equilibrium structure and transient outbreak dynamics, while providing a general framework that links evolutionary behavioral adaptation and epidemic control.
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