Flahault Antoine, Vergu Elisabeta, Coudeville Laurent, Grais Rebecca F
Institut National de la Santé et de la Recherche Médicale (Inserm), Unit 707, WHO Collaborating Centre for Electronic Disease Surveillance, Université Pierre et Marie Curie, 27, rue Chaligny, F-75571 Paris Cedex 12, France.
Vaccine. 2006 Nov 10;24(44-46):6751-5. doi: 10.1016/j.vaccine.2006.05.079. Epub 2006 Jun 12.
Mathematical modelling provides useful insight into the geographic and temporal spread of pandemic influenza. It has been recently used to assess the ability to stop a pandemic at a very early stage. Here, we model the global diffusion of pandemic influenza and the impact of available preventive and control measures. We refined a published SEIR deterministic model of disease dynamics within 52 cities interconnected via air transport to simulate the impact of five interventions in a variety of scenarios: vaccination, case isolation, therapeutic and prophylactic antiviral treatment, and air traffic reduction. The impact of these measures was assessed on the spread of a potential pandemic strain profile, with an average attack-rate of 26%, a case-fatality rate of 2.5% and a residual immunity of 25%. Our analysis highlighted the importance of: (1) a global perspective for dealing with pandemic risks; (2) the time factor and, hence, the importance of surveillance systems; (3) the complementary role of available control measures. Results provide general guidance for the issues of concern to public-health decision-makers: when to set up interventions, where, and at which administrative levels.
数学建模为深入了解大流行性流感的地理和时间传播提供了有用的见解。最近它已被用于评估在极早期阶段阻止大流行的能力。在此，我们对大流行性流感的全球传播以及可用的预防和控制措施的影响进行建模。我们完善了一个已发表的通过航空运输相互连接的52个城市内疾病动态的SEIR确定性模型，以模拟在各种情景下五种干预措施的影响：疫苗接种、病例隔离、治疗性和预防性抗病毒治疗以及空中交通减少。评估了这些措施对一种潜在大流行毒株特征传播的影响，其平均攻击率为26%，病死率为2.5%，残余免疫力为25%。我们的分析突出了以下几点的重要性：（1）应对大流行风险的全球视角；（2）时间因素，以及因此监测系统的重要性；（3）可用控制措施的互补作用。结果为公共卫生决策者关注的问题提供了一般指导：何时、何地以及在哪个行政级别设立干预措施。
