Predictions by early indicators of the time and height of the peaks of yearly influenza outbreaks in Sweden
Predictions by early indicators of the time and height of the peaks of yearly influenza outbreaks in Sweden
复制标题
DOI：
10.1177/1403494808089566
复制
发表时间：
2008-07-01
影响因子：
3.4
通讯作者：
Frisen, Marianne
中科院分区：
文献类型：
--
作者：
Andersson, Eva;Kuhlmann-Berenzon, Sharon;Frisen, Marianne
目的：提出了根据早期观测预测流感高峰的方法。这些预测可用于规划目的。方法：在本研究中，描述了新的可靠方法，并将其应用于瑞典每周流感样疾病（ILI）和每周流感实验室诊断（LDI）的数据。提出了预测LDI峰值时间和峰值高度的简单规则和高级规则。这些预测是使用从早期LDI报告中的数据计算出的协变量做出的。简单规则是基于观测到的LDI值，而高级规则是基于单峰回归的平滑。建议的预测因子通过交叉验证和应用于观测季节进行评估。结果：研究了ILI与LDI之间的关系，发现ILI变量不能很好地代表LDI变量。LDI高峰时间的高级预测规则的中位数误差为0.9周，高峰高度的高级预测规则的中位数偏差为28%。结论：统计预测方法具有实用价值。
Aims: Methods for prediction of the peak of the influenza from early observations are suggested. These predictions can be used for planning purposes. Methods: In this study, new robust methods are described and applied to weekly Swedish data on influenza-like illness (ILI) and weekly laboratory diagnoses of influenza (LDI). Both simple and advanced rules for how to predict the time and height of the peak of LDI are suggested. The predictions are made using covariates calculated from data in early LDI reports. The simple rules are based on the observed LDI values, while the advanced ones are based on smoothing by unimodal regression. The suggested predictors were evaluated by cross-validation and by application to the observed seasons. Results: The relationship between ILI and LDI was investigated, and it was found that the ILI variable is not a good proxy for the LDI variable. The advanced prediction rule regarding the time of the peak of LDI had a median error of 0.9 weeks, and the advanced prediction rule for the height of the peak had a median deviation of 28%. Conclusions: The statistical methods for predictions have practical usefulness.