Using a cloud-based machine-learning classification tree analysis to understand the demographic characteristics associated with COVID-19 booster vaccination among adults in the United States

ABSTRACT

A tree model identified adults aged ≤34 years, Johnson & Johnson primary series recipients, people from racial/ethnic minority groups, residents of non-large metro areas, and those living in socially vulnerable communities in the South as less likely to be boosted. These findings can guide clinical/public health outreach toward specific sub-populations.