Overcoming Vaccine Hesitancy and Preventing Cancer Through Adaptive Learning Artificial Intelligence and Refinement of Reminder Interventions and Campaigns

HPV is common (>80% of people), responsible for 36,000 cancer diagnoses each year in the U.S., and largely preventable. Vaccine hesitancy is a barrier to immunization and misinformation during the COVID-19 pandemic accelerated hesitancy, leading to sharp declines in adolescent immunizations, including HPV vaccination. Efforts focused on childhood vaccination, resulted in deprioritization of HPV and adolescent immunization. Patient reminder and recall (RR) strategies have been proven successful in immunization uptake; however, the effectiveness of these strategies varies by geographic and sociodemographic factors. The current study will be among the first to use state-level vaccination registry data to systematically examine missed opportunities and identify spatial and temporal trends of HPV vaccination. This project will inform the creation of an adaptive learning artificial intelligence for refinement of interactive RR strategies and interventions. Solutions arising from this study are scalable, can be tailored for diverse reminder campaigns, responsive to evolving landscapes, and designed to deliver cost-effective solutions. Both innovative and transformative, this cross-campus collaboration will address complex healthcare problems using precision public health strategies, optimized for decreasing vaccine hesitancy and increasing uptake, and provide preliminary results for high-impact NIH and NCI funding proposals.