[SS05] Data and model driven - study on infectious diseases modelling

[SS05-05] Polarization, Conflict, Pattern Boundaries, and Public Health: Modelling the Impact of Opinion Dynamics on Infectious Disease Spread

Xuzhe Qian¹, *Bo-Wei Qin^1,2, Huaiping Zhu³, Wei Lin^1,2 (1. Fudan University (China), 2. Shanghai Artificial Intelligence Laboratory (China), 3. York University (Canada))

Keywords:

Opinion dynamics,Opinion-disease modelling,Pattern formation

While polarization is often studied in socio-political contexts, its implications for public health—particularly in shaping behavioral responses to infectious diseases—are less explored. This talk focuses on the opinion dynamics and its influence in epidemiology by modelling and investigating how patterns of polarized attitudes (e.g., toward vaccination, social distancing, or masking) evolve and influence disease transmission patterns. We propose a networked dynamical model incorporating black-and-white thinking, a cognitive mechanism that drives opinion consolidation, to simulate how polarized communities emerge and interact during outbreaks. We also demonstrate that social conflict emerges during the spread of opinion and/or infectious diseases. More significantly, we find that conflict is not a direct consequence of polarization but is tightly related to pattern boundaries of clustered opinions. We will also discuss how opinion and disease transmission patterns evolve in different networks and provide insights into developing effective modulation and intervention strategies to reduce social conflict and transmission risk.