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<p>This study identifies optimal, fiscally sustainable HPV vaccination strategies for China using Bayesian optimization and transmission dynamics modeling. By integrating a demographic-based HPV transmission model with a decision-analysis framework, we simulated cervical cancer burden across varying time horizons (30–100 years). Our budget impact analysis, incorporating willingness-to-pay data from a multi-center contingent valuation survey of 787 parents, reveals critical funding dynamics. We found that achieving cervical cancer elimination within 40 years necessitates a 23.97% vaccination coverage among 15–17-year-old girls using the domestic nonavalent vaccine. Conversely, a rapid 30-year elimination target requires 76.66% coverage. At current market prices, autonomous consumer demand falls short, exposing a ¥35.93 billion funding gap for the 40-year target. To mitigate these financial barriers and ensure long-term fiscal resilience, we propose a tripartite financing mechanism—allocating costs among consumers (45.90%), the government (26.19%), and medical insurance (27.91%). These algorithm-driven findings provide an actionable, evidence-based framework for optimizing multi-party health financing and accelerating cervical cancer elimination in China.</p>

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Algorithm-driven HPV vaccine allocation paradigm for cervical cancer elimination targeting the Chinese population

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月19日

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  • Liangru Zhou,
  • Weihua Luo,
  • Ruixi Qin,
  • Di Wang,
  • Peipei Chai,
  • Shuang Ma,
  • Xin Zhang,
  • Guoxiang Liu,
  • Zhiwei Rong

摘要

This study identifies optimal, fiscally sustainable HPV vaccination strategies for China using Bayesian optimization and transmission dynamics modeling. By integrating a demographic-based HPV transmission model with a decision-analysis framework, we simulated cervical cancer burden across varying time horizons (30–100 years). Our budget impact analysis, incorporating willingness-to-pay data from a multi-center contingent valuation survey of 787 parents, reveals critical funding dynamics. We found that achieving cervical cancer elimination within 40 years necessitates a 23.97% vaccination coverage among 15–17-year-old girls using the domestic nonavalent vaccine. Conversely, a rapid 30-year elimination target requires 76.66% coverage. At current market prices, autonomous consumer demand falls short, exposing a ¥35.93 billion funding gap for the 40-year target. To mitigate these financial barriers and ensure long-term fiscal resilience, we propose a tripartite financing mechanism—allocating costs among consumers (45.90%), the government (26.19%), and medical insurance (27.91%). These algorithm-driven findings provide an actionable, evidence-based framework for optimizing multi-party health financing and accelerating cervical cancer elimination in China.