Because vaccine hesitancy is a dynamic trait, it is critical to identify and compare the contributing factors at the different stages of a pandemic. The prediction of vaccine decision making and the interpretation of the analytical relationships among variables that encompass public perceptions and attitudes towards the COVID-19 pandemic have been extensively limited to the studies conducted after the administration of the first FDA-approved vaccine in December of 2020. In order to fill the gap in the literature, we used six predictive models and identified the most important factors, via Gini importance measures, that contribute to the prediction of COVID-19 vaccine acceptors and refusers using a nationwide survey that was administered in November 2020, before the widespread use of COVID-19 vaccines. Concerns about (re)contracting COVID-19 and opinions regarding mandatory face covering were identified as the most important predictors of vaccine decision making. By investigating the vaccine acceptors and refusers before the introduction of COVID-19 vaccines, we can help public health officials design and deliver individually tailored and dynamic vaccination programs that can increase the overall vaccine uptake.
Keywords: COVID-19 vaccination; mask mandate; predictive modeling; vaccine hesitancy.