论文部分内容阅读
目的应用差分自回归移动平均模型(Autoregressive Integrated Moving Average model,ARIMA),分析和预测四川口岸出境人员中乙肝表面抗原(HBsAg)阳性疫情,为制定防治对策和措施提供科学依据。方法利用2007年—2011年四川国际旅行卫生保健中心出境人员HBsAg逐月监测数据,使用SAS9.1统计软件,建立ARIMA模型。结果ARIMA(0,1,1()0,1,1)12模型较好地拟合了既往时间段上的阳性检出率序列,各参数估计均有统计学意义,用该模型进行回代预测,预测检出率与实际检出率吻合程度较高。结论ARIMA模型可用于四川口岸出境人员HBsAg阳性检出率的动态分析和短期预测。
Objective To analyze and predict the prevalence of hepatitis B surface antigen (HBsAg) positive among outbound workers in Sichuan Province by using the Autoregressive Integrated Moving Average model (ARIMA), so as to provide a scientific basis for the development of control strategies and measures. Methods The monthly monitoring data of HBsAg for outbound travelers from Sichuan International Travel Health Care Center from 2007 to 2011 were used to establish the ARIMA model using SAS9.1 statistical software. Results The ARIMA (0, 1, 1 () 0, 1, 1) 12 model fitted the positive detection rate sequence over the past time period well and all parameters were statistically significant. Prediction, forecasting the detection rate and the actual detection rate of a high degree of agreement. Conclusion The ARIMA model can be used for dynamic analysis and short-term prediction of HBsAg positive detection rate among outbound workers in Sichuan.