Using conditional inference to quantify interaction effects of socio-demographic covariates of US COVID-19 vaccine hesitancy.

ABSTRACT: COVID-19 vaccine hesitancy has become a major issue in the U.S. as vaccine supply has outstripped demand and vaccination rates slow down. At least one recent global survey has sought to study the covariates of vaccine acceptance, but an inferential model that makes simultaneous use of several socio-demographic variables has been lacking. This study has two objectives. First, we quantify the associations between common socio-demographic variables (including, but not limited to, age, ethnicity, and income) and vaccine acceptance in the U.S. Second, we use a conditional inference tree to quantify and visualize the interaction and conditional effects of relevant socio-demographic variables, known to be important correlates of vaccine acceptance in the U.S., on vaccine acceptance. We conduct a

SUBMITTER: Shen K 

PROVIDER: S-EPMC10180637 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature