Objectives/Goals: Widespread COVID-19 vaccine hesitancy was a critical barrier to managing the pandemic. Rural populations represent a key demographic in this challenge, yet the specific drivers of their hesitancy remain underexplored. To address this gap, we analyzed a survey of 454 participants in rural Mississippi to identify key predictors of vaccine hesitancy. Methods/Study Population: We employed six machine learning models and a logistic regression model, using feature importance and partial dependence analyses to understand the influence of demographic, behavioral, and belief-based factors. Results/Anticipated Results: Among participants, 98 (21.6%) reported vaccine hesitancy. The Bayesian Additive Regression Trees (BART) model identified vaccine safety as the most critical predictor, with hesitancy probabilities dropping from 0.4 to below 0.1 among those who agreed that vaccines are safe. Different from some other studies, factors such as vaccine accessibility and healthcare provider support had limited influence. Belief in vaccine safety and education level were the primary drivers of vaccine hesitancy in the rural population. Discussion/Significance of Impact: These findings suggest that public health interventions targeting rural communities must better communicate vaccine safety to effectively combat hesitancy.
Ge et al. (Wed,) studied this question.