Stroup D F, Thacker S B, Herndon J L
Division of Surveillance and Epidemiologic Studies, Centers for Disease Control, Atlanta, GA 30333.
Stat Med. 1988 Oct;7(10):1045-59. doi: 10.1002/sim.4780071006.
We employed multiple time series analysis to estimate the impact of influenza on mortality in different age groups, using a procedure for updating estimates as current data become available from national mortality data collected from 1962 to 1983. We compared mortality estimates that resulted from a multivariate model for epidemic forecasting with those obtained from univariate models. We found more accurate prediction of deaths from all age groups using the multivarate model. While the univariate models show an adequate fit to the data, the multivariate model often enables earlier detection of epidemics. Additionally, the multivariate approach provides insight into relationships among different age groups at different points in time. For both models, the largest excess mortality due to pneumonia and influenza during influenza epidemics occurred among those 65 years of age and older. Although multiple time series models appear useful in epidemiologic analysis, the complexity of the modelling process may limit routine application.
我们采用多重时间序列分析来估计流感对不同年龄组死亡率的影响，使用一种程序，随着从1962年至1983年收集的国家死亡率数据中获取当前数据，更新估计值。我们将用于疫情预测的多变量模型得出的死亡率估计值与单变量模型得出的估计值进行了比较。我们发现，使用多变量模型能更准确地预测所有年龄组的死亡情况。虽然单变量模型对数据拟合良好，但多变量模型往往能更早地检测到疫情。此外，多变量方法能洞察不同年龄组在不同时间点之间的关系。对于这两种模型，流感疫情期间因肺炎和流感导致的最大超额死亡率出现在65岁及以上人群中。虽然多重时间序列模型在流行病学分析中似乎很有用，但建模过程的复杂性可能会限制其常规应用。
