COVID-19 Vaccine Hesitancy and Information Diffusion: An Agent-based Modeling Approach
Pooria Taghizadeh Naderi, Ali Asgary, Jude Kong, Jianhong Wu, Fattaneh, Taghiyareh

TL;DR
This study uses an agent-based model to show how information diffusion, especially negative messages, significantly impacts COVID-19 vaccine acceptance and hesitancy, highlighting the importance of opinion dynamics.
Contribution
It introduces a comprehensive agent-based simulation framework to quantify how information diffusion influences vaccine acceptance, incorporating socio-demographics and vaccine types.
Findings
Negative information spread increases vaccine hesitancy
Information diffusion significantly affects vaccine acceptance rates
Model calibrated with Canadian survey data supports the influence of opinions
Abstract
Despite the unprecedented success in the rapid development of several effective vaccines against the Cov-SARS-2, global vaccination rollout efforts suffer from vaccine distribution inequality and vaccine acceptance, leading to insufficient public immunity provided by the vaccine products. While a major current focus in vaccine acceptance research is how to model and inform vaccine acceptance based on social-demographic parameters, characteristics of vaccine acceptance are not well understood and in particular, it is not known whether and how information diffusion influences vaccine acceptance. This study examines how information diffusion can change vaccine acceptance by developing a comprehensive computational model with an agent-based simulation technique to overcome the modeling and quantification complexity associated with socio-demographics, vaccine types, population statistics,…
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Taxonomy
TopicsVaccine Coverage and Hesitancy · COVID-19 epidemiological studies · Misinformation and Its Impacts
