差分自回归移动平均模型在肾综合征出血热发病预测中的应用研究

目的探讨差分自回归移动平均模型（ARIMA）在肾综合征出血热（HFRS）预测分析中的应用。方法用SPSS16．0软件建立1986-2011年河北省HFRS逐月疫情资料数据库，用ARIMA相关模块进行建模拟合并进行预测分析。结果河北省1986-2011年HFRS发病数呈现明显的季节周期性。筛选ARIMA（0，1，1）×（0，1，2）_12模型为最优模型，对河北省2012年各月发病数进行预测，2012年1-12月实际值均落人了预测值的95％可信区间内。结论ARIMA模型可以很好地拟合HFRS发病数的变动趋势，并可用于预测未来疫情，为HFRS防控工作提供依据。

Application of autoregressive integrated moving average model in prediction of hemorrhagic fever with renal syndrome

Objective To evaluate the application of autoregressive integrated moving average （ARIMA） model in the prediction of monthly incidence of hemorrhagic fever with renal syndrome （HFRS）. Methods The database of monthly epidemic situation of HFRS in Hebei province, China from 1986 to 2011 was constructed with SPSS 16.0. A mathematic model was constructed using ARIMA of SPSS 16.0 and used to predict the epidemic situation in 2012. Results The HFRS incidence presented obvious seasonal periodicity during 1986 to 2011 in Hebei province. ARIMA （0, 1, 1）× （0, l, 2）12 model best fitted the incidence of HFRS from January 1986 to December 2011. The actual average incidence of HFRS in 2012 fell within the 95% confidence interval of prediction. Conclusion ARIMA model fits well in the prediction of HFRS incidence, and is suitable for use in epidemiological prediction to provide a basis for the prevention and control of HFRS.