Social norm dynamics in a behavioral epidemic model on multiplex networks

Understanding the social determinants influencing preventive measures adoption during epidemics is crucial for effective disease modeling and policy making. While traditional epidemic models focused on rational decision-making and psychological biases, recent studies highlight the role of social norms. We develop a behavioral epidemic model on a multiplex network, by integrating an Experience Weighted Attractor (EWA) learning mechanism and social norm dynamics. Incorporating social norms in our decision-making mechanism significantly reduces final infected fractions, offering an alternative to altruism for boosting vaccination coverage. Furthermore, we examine the importance of the dynamics of each one of the social norms, injunctive or descriptive, in reducing the infected fraction, finding that the former has a more significant effect in agreement with some experimental evidence. We also explore the effect of external interventions on epidemic expansion, aiding in refining public communication protocols. Enhanced models of social norm dynamics, if validated and tested, can better capture the complexities of human social behavior and mitigate various societal challenges beyond pandemics.