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1. 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.

Author

Meng, Lu, Fast, Hannah E, Saelee, Ryan, Zell, Elizabeth, Murthy, Bhavini Patel, Murthy, Neil Chandra, Lu, Peng-Jun, Shaw, Lauren, Harris, LaTreace, Gibbs-Scharf, Lynn, and Chorba, Terence

Abstract

A tree model identified adults age ≤34 years, Johnson & Johnson primary series recipients, people from racial/ethnic minority groups, residents of nonlarge 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 subpopulations. [ABSTRACT FROM AUTHOR]

Published
2022
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