Predictive Models for Biomedicine & Environment, Bruno Kessler Foundation, Trento, Italy.
Epidemiol Infect. 2011 Jan;139(1):68-79. doi: 10.1017/S0950268810001317. Epub 2010 Jun 14.
We describe the real-time modelling analysis conducted in Italy during the early phases of the 2009 A/H1N1v influenza pandemic in order to estimate the impact of the pandemic and of the related mitigation measures implemented. Results are presented along with a comparison with epidemiological surveillance data which subsequently became available. Simulated epidemics were fitted to the estimated number of influenza-like syndromes collected within the Italian sentinel surveillance systems and showed good agreement with the timing of the observed epidemic. On the basis of the model predictions, we estimated the underreporting factor of the influenza surveillance system to be in the range 3·3-3·7 depending on the scenario considered. Model prediction suggested that the epidemic would peak in early November. These predictions have proved to be a valuable support for public health policy-makers in planning interventions for mitigating the spread of the pandemic.
我们描述了意大利在 2009 年甲型 H1N1v 流感大流行早期进行的实时建模分析,以估计大流行的影响和实施的相关缓解措施。结果与随后可用的流行病学监测数据进行了比较。模拟的疫情与在意大利哨点监测系统中收集的流感样综合征估计数量相吻合,与观察到的疫情时间吻合较好。基于模型预测,我们估计流感监测系统的漏报率在考虑到的不同情景下在 3.3-3.7 之间。模型预测表明,疫情将在 11 月初达到高峰。这些预测为公共卫生政策制定者规划缓解大流行传播的干预措施提供了有价值的支持。