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Paper Information

Title

Unraveling vaccination behavior under misinformation in homogeneous and heterogeneous populations via integrated dynamical and network models.

Abstract

Misinformation about vaccination poses a significant public health threat by reducing vaccination rates and increasing disease burden. Understanding population heterogeneity can aid in recognizing and mitigating the effects of such misinformation, especially when vaccine effectiveness is low. Our research quantifies the impact of misinformation on vaccination uptake and explores its effects in heterogeneous versus homogeneous populations. We employed a dual approach combining compartmental modeling and complex network analysis to examine how various epidemiological parameters influence disease spread and vaccination behaviour. Our results indicate that misinformation significantly lowers vaccination rates, particularly in homogeneous populations, while heterogeneous populations demonstrate greater resilience. Among network topologies, small-world networks achieve higher vaccination rates under varying vaccine efficacies, whereas scale-free networks experience reduced vaccine coverage with higher misinformation amplification. Notably, cumulative infection remains independent of the disease transmission rate when the vaccine is partially effective. In small-world networks, cumulative infection shows high stochasticity across vaccination rates and misinformation parameters, while cumulative vaccination is highest with higher vaccination rates and lower misinformation coefficients. Public health efforts should prioritize addressing misinformation to control disease spread, particularly in homogeneous populations and scale-free networks, where its impact is more severe. Additionally, our model demonstrates strong performance on real-world contact networks, capturing how rapid misinformation spread and limited vaccine efficacy can severely hinder vaccination uptake and accelerate infection rates. Building resilience by fostering diverse community networks and promoting reliable vaccine information can boost vaccination rates. Furthermore, focusing public health campaigns on small-world networks may result in higher vaccine uptake, even when vaccine efficacy varies. These insights can help public health policymakers design effective vaccination strategies that consider population heterogeneity.

Journal

Computers in biology and medicine

Citation

MIDAS Authors