乘积季节ARIMA模型在结核病发病率预测中应用  

Application of multiple seasonal ARIMA model in prediction of tuberculosis incidence

作　　者：杨召[1] 叶中辉[1] 尤爱国[2] 郭奕瑞[1] 张肖肖[2] 梁淑英 邢进[2] 王重建[1] 

机构地区：[1]郑州大学公共卫生学院流行病与卫生统计学系,河南郑州450001 [2]河南省疾病预防控制中心 [3]河南省医学科学院

出　　处：《中国公共卫生》2013年第4期469-472,共4页Chinese Journal of Public Health

基　　金：国家自然科学基金(81001293);河南省科技攻关计划项目(122102310210)

摘　　要：目的探讨乘积季节自回归移动平均(ARIMA)模型在结核病疫情预测的可行性。方法利用某省2004年1月—2011年6月结核病疫情监测资料建立乘积季节ARIMA预测模型,选取2011年7—12月的疫情资料评价模型的预测效能。结果该省2004年1月—2011年12月结核病的发病率呈现明显的季节效应,且发病率逐年小幅递减;乘积季节ARIMA(1,1,0)×(1,1,0)12模型能较好拟合既往时间段内结核病的发病率,且对2011年7—12月结核病月发病率的预测值与实际值基本吻合,平均误差绝对值及平均误差绝对率分别为0.317和4.77%。结论乘积季节ARIMA模型能较好模拟、预测结核病的发病疫情,具有较好的推广应用价值。Objective To explore the feasibility of multiple seasonal autoregressive integrated moving average （ARIMA） model to predict tuberculosis incidence. Methods Multiple seasonal AR1MA（p,d,q） × （P,D,Q） s model was built using tuberculosis surveillance data from January 1,2004 to June 30,2011 in Henan province, and the predictive performance was conducted and assessed using the data from July 1 to December 31,2011. Results The seasonal effect in the incidence of tuberculosis was observed from January 1,2004 to December 31,2011 in the province, and the inci- dence was slightly decreased over time. Multiple seasonal ARIMA（ 1,1,0）×（1,1,0） 12 model could better fit the inci- dence of tuberculosis over the period, and the forecast values were consistent with the actual number, with the average absolute error and the average absolute error rate of 0.317 and 4.77% ,respectively. Conclusion Multiple seasonal ARI- MA model could successfully fit and predict the incidence of tuberculosis, which could be applied for the prevention and control of tuberculosis.

关 键 词：乘积季节自回归移动平均(ARIMA)模型 结核病 发病率 预测 

分 类 号：R521[医药卫生—内科学]