Abstract
BACKGROUND: Seasonal influenza vaccination rates are very low among teenagers. OBJECTIVES: We used publicly available data from the NIS-Teen annual national immunization survey to explore factors that influence the likelihood of a teen receiving their seasonal flu shot. METHODS: Traditional stepwise multivariable regression was used in tandem with machine learning to determine the predictive factors in teen vaccine uptake. RESULTS AND CONCLUSIONS: Age was the largest predictor, with older teens being much less likely to be vaccinated than younger teens (97.48% compared to 41.71%, p < 0.0001). Provider participation in government programs such as Vaccines for Children and the state vaccine registry positively impacts vaccine uptake (p < 0.0001). Identifying as non-Hispanic Black was a small, negative predictor of teen vaccine uptake (78.18% unvaccinated compared to 73.78% of White teens, p < 0.0001). The state quartile for COVID-19 vaccine uptake also strongly predicted flu vaccine uptake, with the upper quartile of state COVID-19 vaccine uptake being significantly more likely to also get vaccinated for influenza (76.96%, 74.94%, 74.55%, and 72.97%, p < 0.0001). Other significant factors are the number of providers, education of the mother, poverty status, and having a mixed provider facility type. Additionally, the multivariable regression analysis revealed little difference in the predictive factors of vaccine uptake between pre- and post-pandemic datasets.