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This study examines how public opinion about vaccination affects epidemic spread on heterogeneous social networks, where individual vaccination decisions are influenced by both peer interactions and local observation of infection rates. Using computational simulations and mathematical modeling on scale-free networks, researchers found that when risk perception from observed infections dominates over peer influence, it increases pro-vaccination sentiment and reduces infection levels, while dominant peer influence can sustain higher infection rates. The work provides analytical expressions for critical infection thresholds and vaccination equilibria that account for the interplay between social network structure and opinion dynamics.
Why it matters
The findings highlight that effective vaccination campaigns must consider not only vaccine distribution but also the social network structure and mechanisms of opinion formation within communities. Understanding how local risk perception versus peer influence shapes vaccination behavior can help public health officials design better communication strategies and interventions to improve vaccination uptake during epidemics.
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arXiv:2603.24403v2 Announce Type: replace
Abstract: Vaccination campaigns play a pivotal role in controlling infectious diseases. Their success, however, depends not only on vaccine efficacy and availability but also significantly on public opinion and the willingness of individuals to vaccinate. This paper investigates a coupled opinion-epidemic model on heterogeneous networks, where individual opinions influence vaccination probability, and opinions themselves evolve through a combination of peer interaction and local risk perception derived from observed infection rates. Embedding the coupled dynamics in scale-free networks, particularly barabasi-Albert structures, allows us to examine the role of network heterogeneity beyond homogeneous-mixing assumptions. Using Monte Carlo simulations and a semi-analytical microscopic Markov-chain approach, we derive and numerically validate analytical expressions for the critical infection threshold and stable vaccinated population where risk perception dominated peer influence. Our results show that stronger local risk perception enhances pro-vaccination opinions and suppresses infection, while dominant peer influence can increase long-term infection levels. These findings underscore the importance of accounting for social behavior and network structure when designing effective vaccination and epidemic control strategies.
Source: Opinion-Driven Vaccination and Epidemic Dynamics on Heterogeneous Networks