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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.


Current Status

2025-02-04
Title: Overcoming Vaccine Hesitancy and Preventing Cancer Through Adaptive Learning Artificial Intelligence and Refinement of Reminder Interventions and Campaigns

Background: Despite HPV vaccination preventing six cancers and being recommended for over a decade, uptake remains low in the U.S. and Utah, even as oropharyngeal cancer incidence (59,000 in 2025) surpasses cervical cancer, rising most rapidly among men, especially non-Hispanic white men.
Methods: Evaluated sociodemographic factors and trends of HPV missed vaccination opportunities (HPV-MVOs) among children/adolescents (C/A) 9-18 years old in the Utah Immunization Information System (USIIS) over 5.5 years. Examined the impact of rurality on HPV-MVOs among n=685,614 C/A and explored ethnicity as a moderator. Conducted logistic regression, mediation analyses, and EMM (Effect Measure Modification) using R.
Results: During 2017-2023, 70% of Utah adolescents had at least one HPV-MVO, averaging 2.14(SD=1.56) per individual. Those who were Latino/a (aOR=1.26 [95%CI: 1.13-1.42]), those with stable insurance (aOR=1.15 [95% CI: 1.14-1.16]), and those in rural areas (aOR=1.04 [95% CI: 1.02-1.06]) had higher odds of an HPV-MVO. Insurance stability mediated 17.7% of the effect of rurality on HPV-MVO, with the indirect effect moderated by race and ethnicity (p<.0001).
Conclusion: Rurality, race, and ethnicity are significant and relevant factors of HPV-MVO. Insurance mediates the effect of rurality on HPV-MVO and interacts differently across racial and ethnic groups, highlighting the need for tailored interventions.

Collaborators

DEANNA KEPKA
College of Nursing
CON DACC DIVISION
Project Owner

SIMON BREWER
College of Social and Behavioral Science
Geography

BENJAMIN HAALAND
School of Medicine
Population Health Sciences

Naina Phadnis
College of Science
School of Biological Sciences

ECHO WARNER
College of Nursing
CON DACC DIVISION

Project Info

Funded Project Amount
$15K

Keywords
1. Vaccine Hesitancy 2. HPV Vaccination 3. Cancer Prevention 4. Sociodemographic disparities 5. Rural disparities 6. USIIS (Utah Statewide Immunization Information System) 7. Reminder and Recall 8. Adaptive and Machine Learning 9. Artificial Intelligence 10. Individual-level 11. Spatio-temporal trends 12. Geographic or spatial trends 13. Statewide Systems Approach 14. Adaptive text-message RCT 15. Precision Public Health 16. Transformative healthcare 17. Healthcare systems delivery

Project Status
Funded 2023

Poster
View poster (pdf)
Last Updated: 9/1/21