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State-level disparities in cervical cancer prevention and outcomes in the U.S.: A modeling study
Fernando Alarid-Escudero1, Valeria Gracia2, Marina Wolf3
1Department of Health Policy, School of Medicine, and Stanford Health Policy, Freeman-Spogli Institute for International Studies, Stanford University, Stanford, CA, USA.
Background:
Despite HPV vaccines' availability for over a decade, coverage across the US varies. While 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 US 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 <4 per 100k women.
Results:
Increasing vaccination coverage to 80% in Texas over ten 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 (Crl:0.66-1.53) per 100,000 women, and California a 24.4% (CrI:20.0-30.0%) reduction, from 1.01 (Crl:0.66-1.44) to 0.76 (Crl:0.50-1.09) per 100,000 women. Achieving 80% coverage in five years will provide slightly larger and sooner reductions. If the vaccination coverage levels in 2019 continue, cervical cancer elimination could occur nationally by 2051 (Crl: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.
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