Forecasting seasonal outbreaks of influenza
Forecasting seasonal outbreaks of influenza
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DOI：
10.1073/pnas.1208772109
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发表时间：
2012-12-11
影响因子：
11.1
通讯作者：
Karspeck, Alicia
中科院分区：
文献类型：
--
作者：
Shaman, Jeffrey;Karspeck, Alicia
流感在世界温带地区季节性复发;然而，我们预测局部季节性流感爆发的时间、持续时间和规模的能力仍然有限。在这里，我们开发了一个框架，用于初始化季节性流感爆发的实时预报，使用数值天气预报中常用的数据同化技术。对当地流感感染率的实时、基于网络的估计使这种类型的定量预测成为可能。在同化这些基于网络的估计之后，每周生成纽约市2003-2008年流感季节的回顾性集合预报。研究结果表明，实时熟练的预测高峰时间可以提前7周以上的实际高峰。此外，对这些预测的信心可以从预报集合的传播中推断出来。这项工作是开发季节性流感实时预测统计严格系统的第一步。
Influenza recurs seasonally in temperate regions of the world; however, our ability to predict the timing, duration, and magnitude of local seasonal outbreaks of influenza remains limited. Here we develop a framework for initializing real-time forecasts of seasonal influenza outbreaks, using a data assimilation technique commonly applied in numerical weather prediction. The availability of real-time, web-based estimates of local influenza infection rates makes this type of quantitative forecasting possible. Retrospective ensemble forecasts are generated on a weekly basis following assimilation of these web-based estimates for the 2003-2008 influenza seasons in New York City. The findings indicate that real-time skillful predictions of peak timing can be made more than 7 wk in advance of the actual peak. In addition, confidence in those predictions can be inferred from the spread of the forecast ensemble. This work represents an initial step in the development of a statistically rigorous system for real-time forecast of seasonal influenza.