基于马尔科夫模型的深圳市60岁及以上人群接种流感疫苗的成本效果分析

目的评估深圳市≥60岁人群免费接种流感疫苗的成本效果。方法以深圳市≥60岁常住人群为研究对象, 构建马尔科夫状态转换模型, 从社会的角度来评估与不接种疫苗相比, 每年接种流感疫苗预防流感的成本效果。模型以周为周期, 研究时限5年, 模拟流感发病的季节性变化。采用5%的年贴现率对模型中的成本和质量调整生命年(QALYs)进行贴现并计算净货币效益(NMB), 以2019年中国人均国内生产总值GDP(70 892元)作为支付意愿阈值进行评价。单因素和概率敏感性分析用于评估参数不确定性对结果的影响。结果与不接种疫苗相比, 人均节约总成本35元并且多获得0.007个QALYs, 人均获得的NMB为529元。单因素敏感性分析的结果显示, 流感发病率和流感疫苗保护效果是影响基线结果的主要因素。在1 000次的蒙特卡罗模拟中, 接种流感疫苗具有成本效果的概率为100%。结论与不接种疫苗相比, 深圳市≥60岁人群每年接种流感疫苗是一项成本节约的疾病预防策略。

Based on a Markov model, cost-effectiveness analysis of influenza vaccination among people aged 60 years and older in Shenzhen

Objective To assess the cost-effectiveness of influenza vaccination among people aged 60 years and older in Shenzhen. Methods A Markov state transition model was constructed to evaluate the cost-effectiveness of annual influenza vaccination for preventing influenza infection compared with no vaccination among the elderly from the social perspective. Allowing seasonal variation of influenza activity, the model followed a five-year cohort using weekly cycles. We employed once the Chinese gross domestic product (GDP) per capita in 2019 (70 892 yuan) as the willingness-to-pay (WTP) threshold and calculated the net monetary benefit (NMB) with costs and quality-adjusted life-years (QALYs) discounted at 5% annually. The impact of parameter uncertainty on the results was examined using one-way and probabilistic sensitivity analyses (PSA). Results The base case amounted to approximately 35 yuan of cost-saving and a net gain of 0.007 QALYs. Correspondingly, the NMB was 529 yuan per vaccinated person. One-way sensitivity analyses showed that the NMB was relatively sensitive to changes in the attack rate of influenza and vaccine effectiveness. Based on the results of PSA with 1 000 Monte Carlo simulations, influenza vaccination had a probability of being cost-effective in 100% of the repetitions.Conclusions The present study provides evidence that influenza vaccination is a cost-saving disease prevention strategy for people aged 60 years and older in Shenzhen.