Real-time epidemic forecasting for pandemic influenza
Real-time epidemic forecasting for pandemic influenza
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DOI：
10.1017/s0950268806007084
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发表时间：
2007-04-01
影响因子：
4.2
通讯作者：
Leach, S.
中科院分区：
文献类型：
--
作者：
Hall, I. M.;Gani, R.;Leach, S.
H5N1流感病毒在鸟类中的持续全球传播增加了对新的人流感大流行的担忧，计划或正在实施一些监测举措，以近实时监测大流行的影响。使用流行病学数据收集在爆发的早期阶段，我们展示了如何预测的大流行波的最大流行率的时间，沿着，其幅度和持续时间，可以通过拟合一个大规模行动的流行病模型的监测数据，通过标准回归分析。这种方法是通过应用该模型的常规数据收集在英国在不同的波的前三次大流行的验证。该方法在预测历史流行率方面的成功表明，此类暴发与理论模型相当吻合，这一因素可在未来的大流行中加以利用，以更新正在进行的规划和应对措施。
The ongoing worldwide spread of the H5N1 influenza virus in birds has increased concerns of a new human influenza pandemic and a number of surveillance initiatives are planned, or are in place, to monitor the impact of a pandemic in near real-time. Using epidemiological data collected during the early stages of an outbreak, we show how the timing of the maximum prevalence of the pandemic wave, along with its amplitude and duration, might be predicted by fitting a mass-action epidemic model to the surveillance data by standard regression analysis. This method is validated by applying the model to routine data collected in the United Kingdom during the different waves of the previous three pandemics. The success of the method in forecasting historical prevalence suggests that such outbreaks conform reasonably well to the theoretical model, a factor which may be exploited in a future pandemic to update ongoing planning and response.