| Full text | |
| Author(s): |
Iasulaitis, Sylvia
;
Valejo, Alan Demetrius Baria
;
dos Santos, Leonardo Ribeiro
Total Authors: 3
|
| Document type: | Journal article |
| Source: | VACCINE: X; v. 26, p. 11-pg., 2025-10-25. |
| Abstract | |
This study identifies the underlying drivers of vaccine hesitancy by analyzing political factors, perceptions of vaccine safety, socioeconomic characteristics, and communication variables. We created a partisanship score using supervised machine learning algorithms with the random forest method to assess the influence of political orientations on the roots of COVID-19 vaccine rejection attitudes. This score was then tested empirically using sociodemographic data from a public opinion survey conducted with a sample of the Brazilian population. Based on the weight of evidence (WoE), the attribute relevance analysis revealed key characteristics of citizens who rejected the COVID-19 vaccine in Brazil, highlighting perceptions of vaccine safety and political variables. The data showed that citizens more loyal to then-president Jair Bolsonaro, a vocal vaccine skeptic, were less likely to get vaccinated. They also demonstrated higher perceptions of vaccine-related risks and were more prone to believing in conspiracy theories and misinformation surrounding the vaccine. The methodology developed in this study can be applied to other populations globally to better understand the roots of anti-vaccine attitudes, particularly the influence of political factors. (AU) | |
| FAPESP's process: | 22/03090-0 - Analysis of large amounts of political data and complex networks: mining modelling and applications in Computational Political Science |
| Grantee: | Sylvia Iasulaitis |
| Support Opportunities: | Research Grants - Initial Project |