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目的探讨时间序列分析中自回归移动平均模型在六安市细菌性痢疾发病预测的可行性和适用性,为早期做好防控工作提供科学依据。方法使用SPSS 17.0软件对六安市2003年1月～2012年12月的细菌性痢疾月发病率建立ARIMA模型,以2013年的1～7月实际发病率作为预测模型的考核样本,验证模型的预测效果。结果六安市细菌性痢疾月发病率模型为ARIMA(0,0,1)×(0,1,1)12,模型移动平均参数MA1=-0.473(t=-5.153,P<0.05),季节移动平均参数SMA1=0.937(t=2.494,P=0.014);残差分析Ljung-BoxQ统计量经检验,差异无统计学意义(Ljung-BoxQ=10.208,P=0.856),提示残差为白噪声。模型预测的平均相对误差为27.82%,但预测的动态趋势与实际值基本吻合,且实际值均在预测值的95%可信区间内。结论 ARIMA(0,0,1)×(0,1,1)12模型可为六安市细菌性痢疾的防控提供参考。
Objective To explore the feasibility and applicability of the autoregressive moving average model for predicting the incidence of bacterial dysentery in Luan City in time series analysis, and to provide scientific evidence for early prevention and control. Methods The SPSS 17.0 software was used to establish the ARIMA model for the monthly incidence of bacterial dysentery from January 2003 to December 2012 in Lu’an City. The actual incidence from January to July in 2013 was used as the assessment sample of the prediction model to verify the model. Forecast effect. Results The monthly incidence rate of bacterial dysentery in Lu’an City was ARIMA(0,0,1)×(0,1,1)12, and the model moving average parameter MA1=-0.473(t=-5.153, P<0.05). The moving average parameter SMA1=0.937 (t=2.494, P=0.014); the residual analysis Ljung-BoxQ statistic was tested and the difference was not statistically significant (Ljung-BoxQ=10.208, P=0.856), suggesting that the residual was white noise . The average relative error of the model prediction is 27.82%, but the predicted dynamic trend is basically consistent with the actual value, and the actual value is within the 95% confidence interval of the predicted value. Conclusion The ARIMA(0,0,1)×(0,1,1)12 model can provide reference for the prevention and control of bacterial dysentery in Lu’an City.