Real-time influenza forecasts during the 2012-2013 season.
Real-time influenza forecasts during the 2012-2013 season.
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DOI：
10.1038/ncomms3837
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发表时间：
2013
影响因子：
16.6
通讯作者：
Lipsitch, Marc
中科院分区：
文献类型：
--
作者：
Shaman, Jeffrey;Karspeck, Alicia;Yang, Wan;Tamerius, James;Lipsitch, Marc
最近，我们开发了一个季节性流感预测系统，该系统使用先进的数据同化技术和流感发病率的实时估计来优化和初始化基于人群的流感传播动力学数学模型。该系统用于生成和评估纽约市流感高峰时间的回顾性预测。在这里，我们提出了在最近的2012-2013年季节，美国108个城市的季节性流感发展和运行的真实的时间的每周预测。对流感爆发高峰时间进行了可靠的集合预报，预报时间长达9周。随着季节的推移，预测的准确性也在提高，而且预测的效果明显优于其他的模拟预测方法。到第52周，在大多数城市达到峰值之前，63%的集合预报是准确的。据我们所知，这是第一次在真实的时间内对季节性流感进行预测，并证明其准确性。
Recently, we developed a seasonal influenza prediction system that uses an advanced data assimilation technique and real-time estimates of influenza incidence to optimize and initialize a population-based mathematical model of influenza transmission dynamics. This system was used to generate and evaluate retrospective forecasts of influenza peak timing in New York City. Here we present weekly forecasts of seasonal influenza developed and run in real time for 108 cites in the United States during the recent 2012–2013 season. Reliable ensemble forecasts of influenza outbreak peak timing with leads of up to 9 weeks were produced. Forecast accuracy increased as the season progressed, and the forecasts significantly outperformed alternate, analog prediction methods. By Week 52, prior to peak for the majority of cities, 63% of all ensemble forecasts were accurate. To our knowledge, this is the first time predictions of seasonal influenza have been made in real time and with demonstrated accuracy.
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影响因子：
4.4
作者：
Cosgrove, BA;Lohmann, D;Meng, J
通讯作者：
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影响因子：
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作者：
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作者：
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DOI：
10.1073/pnas.0806852106
发表时间：
2009-03-03
影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
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