Analysis of causal relations between vaccine hesitancy for COVID-19 vaccines and ideological orientations in Brazil

Abstract

This article presents a causal inference analysis of vaccine hesitancy for Coronavirus disease 2019 (COVID-19) vaccines based on socio-demographic data obtained via questionnaires applied to a sample of the Brazilian population. This data includes the respondents' political preferences, age group, education, salary range, country region, sex, believing fake news, vaccine confidence, and intention to get the COVID-19 vaccine. The research created a causal graph using these variables, seeking to answer questions about the probability of people getting vaccinated. The results of this research corroborate findings observed in the literature, also presenting unique findings: (i) The perception that the vaccine is safe is positively affected by age group and negatively by religion; (ii) The older the person, the greater the probability of considering the vaccine safe and, consequently, of getting vaccinated; (iii) The religion variable showed great importance in the model since it has a simultaneous causal effect on political preferences and the perception of vaccine safety; (iv) The data reveal that the probability of a person accepting the vaccination against COVID-19 is reduced given the fact that they believe fake news related to the vaccine. The methodology applied in this research can be replicated for populations from other countries so that it is possible to generate customized models. General causal models can be helpful for agencies dealing with vaccine hesitancy to decide which variables should be addressed to reduce this phenomenon.

Keywords: Causal Model; Demographics; Public trust; Risk perception; Social influence; Vaccine hesitancy.