{"doi":"10.1101/2024.06.11.24308795","title":"State-level disparities in cervical cancer prevention and outcomes in the U.S.: A modeling study","abstract":"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.","journal":"medRxiv","year":2024,"id":498412,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8896,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":271684,"name":"Valeria Gracia","orcid":"0000-0003-4853-2922","position":1,"is_corresponding":false},{"id":715390,"name":"Marina E. Wolf","orcid":"0000-0001-9129-3432","position":2,"is_corresponding":false},{"id":674303,"name":"Ran Zhao","orcid":"0000-0001-9539-8274","position":3,"is_corresponding":false},{"id":1303486,"name":"Caleb Easterly","orcid":"0000-0001-7853-377X","position":4,"is_corresponding":false},{"id":107385,"name":"Jane J. Kim","orcid":"0000-0002-9892-9170","position":5,"is_corresponding":false},{"id":314259,"name":"Karen Canfell","orcid":"0000-0002-6443-6618","position":6,"is_corresponding":false},{"id":314257,"name":"Inge M.C.M. de Kok","orcid":"0000-0002-9419-0452","position":7,"is_corresponding":false},{"id":315406,"name":"Ruanne V. Barnabas","orcid":"0000-0002-1793-6003","position":8,"is_corresponding":false},{"id":314256,"name":"Shalini Kulasingam","orcid":"0000-0002-0932-9166","position":9,"is_corresponding":false},{"id":271680,"name":"Fernando Alarid‐Escudero","orcid":"0000-0001-5076-1172","position":0,"is_corresponding":true}],"reference_count":29,"raw_metadata":null,"created_at":"2026-07-19T02:09:42.181447Z","pmid":"38947042","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}