Doyle Aoife, Bonmarin Isabelle, Lévy-Bruhl Daniel, Le Strat Yann, Desenclos Jean-Claude
EPIET and Institut de Veille Sanitaire, France.
J Epidemiol Community Health. 2006 May;60(5):399-404. doi: 10.1136/jech.2005.034082.
Influenza pandemics result in excess mortality and social disruption. To assist health authorities update the French pandemic plan, the authors estimated the number of health events (cases, hospitalisations, and deaths) in a pandemic and compared interventions in terms of impact and efficiency.
A Monte Carlo simulation model, incorporating probability distributions of key variables, provided estimates of health events (HE) by age and risk group. Input variables were set after literature and expert consultation. The impact of targeted influenza vaccination and antiviral prophylaxis/treatment (oseltamivir) in high risk groups (elderly, chronic diseases), priority (essential professionals), and total populations was compared. Outcome measures were HE avoided, number of doses needed, and direct cost per HE avoided.
Without intervention, an influenza pandemic could result in 14.9 million cases, 0.12 million deaths, and 0.6 million hospitalisations in France. Twenty four per cent of deaths and 40% of hospitalisations would be among high risk groups. With a 25% attack rate, 2000-86,000 deaths could be avoided, depending on population targeted and intervention. If available initially, vaccination of the total population is preferred. If not, for priority populations, seasonal prophylaxis seems the best strategy. For high risk groups, antiviral treatment, although less effective, seems more feasible and cost effective than prophylaxis (respectively 29% deaths avoided; 1800 doses/death avoided and 56% deaths avoided; 18,500 doses/death avoided) and should be chosen, especially if limited drug availability.
The results suggest a strong role for antivirals in an influenza pandemic. While this model can compare the impact of different intervention strategies, there remains uncertainty surrounding key variables.
流感大流行会导致额外的死亡和社会混乱。为协助卫生当局更新法国的大流行计划，作者估算了大流行期间的健康事件（病例、住院和死亡）数量，并比较了不同干预措施的影响和效率。
采用蒙特卡洛模拟模型，纳入关键变量的概率分布，按年龄和风险组估算健康事件（HE）。输入变量经文献研究和专家咨询后设定。比较了在高危人群（老年人、慢性病患者）、重点人群（关键职业人员）和总人口中进行针对性流感疫苗接种及抗病毒预防/治疗（奥司他韦）的影响。结果指标包括避免的健康事件数量、所需剂量数以及避免每例健康事件的直接成本。
在无干预情况下，法国的流感大流行可能导致1490万例病例、12万例死亡和60万例住院。24%的死亡和40%的住院发生在高危人群中。若攻击率为25%，根据目标人群和干预措施的不同，可避免2000至86000例死亡。若一开始就有疫苗，优先对总人口进行接种。若没有，则对重点人群而言，季节性预防似乎是最佳策略。对于高危人群，抗病毒治疗虽然效果稍差，但比预防更可行且更具成本效益（分别可避免29%的死亡；每避免一例死亡需1800剂和可避免56%的死亡；每避免一例死亡需18500剂），应予以选择，尤其是在药物供应有限的情况下。
结果表明抗病毒药物在流感大流行中可发挥重要作用。虽然该模型可比较不同干预策略的影响，但关键变量仍存在不确定性。
