State-level disparities in cervical cancer prevention and outcomes in the United States: a modeling study
Discuss this preprint
Start a discussion What are Sciety discussions?Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Background
Despite human papillomavirus (HPV) vaccines’ availability for over a decade, coverage across the United States varies. Although some states have tried to increase HPV vaccination coverage, most model-based analyses focus on national impacts. We evaluated hypothetical changes in HPV vaccination coverage at the national and state levels for California, New York, and Texas using a mathematical model.
Methods
We developed a new mathematical model of HPV transmission and cervical cancer, creating national- and state-level models, incorporating country- and state-specific vaccination coverage and cervical cancer incidence and mortality. We quantified the national- and state-level impact of increasing HPV vaccination coverage to 80% by 2025 or 2030 on cervical cancer outcomes and the time to elimination defined as less than 4 per 100 000 women.
Results
Increasing vaccination coverage to 80% in Texas over 10 years could reduce cervical cancer incidence by 50.9% (95% credible interval [CrI] = 46.6%-56.1%) by 2100, from 1.58 (CrI = 1.19-2.09) to 0.78 (CrI = 0.57-1.02) per 100 000 women. Similarly, New York could see a 27.3% (CrI = 23.9%-31.5%) reduction from 1.43 (CrI = 0.93-2.07) to 1.04 (CrI = 0.66-1.53) per 100 000 women, and California a 24.4% (CrI = 20.0%-30.0%) reduction from 1.01 (CrI = 0.66-1.44) to 0.76 (CrI = 0.50-1.09) per 100 000 women. Achieving 80% coverage in 5 years will provide slightly larger and sooner reductions. If the vaccination coverage levels in 2019 continue, cervical cancer elimination could occur nationally by 2051 (CrI = 2034-2064), but state timelines may vary by decades.
Conclusion
Targeting an HPV vaccination coverage of 80% by 2030 will disproportionately benefit states with low coverage and higher cervical cancer incidence. Geographically focused analyses can better inform priorities.