目的 探讨时间序列模型预测传染性疾病发病率的可行性,应用时间序列求和自回归移动平均(ARIMA)模型对江西省结核病发病率进行预测,为制定结核病防治策略提供依据。 方法 利用ARIMA乘积季节模型(p,d,q)(P,D,Q)s对2006-2011年江西省结核病分月发病数据进行ARIMA模型的建立与分析,并对预测效果进行评价。 结果 江西省2006-2011年结核病分月发病数即含有长期递减趋势又含有以年为周期的季节效应,拟合的相对最佳模型为ARIMA(0,1,1)(0,1,1)12。 结论 ARIMA乘积季节模型能有效的预测江西省结核病发病率的短期变化趋势。
Objective To explore the feasibility of time series model to predict the incidence of infectious diseases, predict the incidence of tuberculosis (TB) in Jiangxi province with ARIMA model and provide scientific evidence for the prevention and treatment of TB. Methods The incidence data of TB in Jiangxi from January 2006 to December 2010 were used to set up ARIMA model and the analyzed by using SAS 9.2. The predictive effect was evaluated. Results The case curve was not only with a long-term descending trend but also with annual seasonality. The relative optimum fitting model was ARIMA (0,1,1)* (0,1,1)12. Conclusion Model of multiple seasonal ARIMA can be used to appropriately predict the change of the TB incidence in short-term in Jiangxi.