Towards a predictive model of COVID-19 vaccine hesitancy among American adults.

ABSTRACT: Designing effective public health campaigns to combat COVID-19 vaccine hesitancy requires an understanding of i) who the vaccine hesitant population is, and ii) the determinants of said population's hesitancy. While researchers have identified a number of variables associated with COVID-19 vaccine hesitancy that could inform such campaigns, little is known about the cumulative or relative predictive power of these factors. In this article, we employ a machine learning model to analyze online survey data collected from 3353 respondents. The model incorporates an array of variables that have been shown to impact vaccine hesitancy, allowing us to i) test how well we can predict vaccine hesitancy, and ii) compare the relative predictive impact of each covariate. The model allows us to correctl

SUBMITTER: Mewhirter J 

PROVIDER: S-EPMC8832389 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature