论文部分内容阅读
目的尝试构建适用于北京市西城区细菌性痢疾发病特点的统计预测模型,为该区传染病定量预测的实施做出探索。方法应用SPSS 13.0统计软件对北京市西城区2004年1月-2013年12月细菌性痢疾逐月发病情况进行求和自回归滑动平均模型(ARIMA)建模和拟合,利用筛选出的最优模型对2014年1-12月的发病情况进行预测,并评价模型的预测效果。结果筛选的最优乘积模型为ARIMA(1,0,0)(0,1,1)_(12),BIC=27.426,模型拟合效果的度量Box-Ljung Q差异无统计学意义(Q=10.949,P=0.813),模型残差序列为白噪声。模型预测值与实际值拟合较好,实际值均在预测值95%可信区间范围内。结论 ARIMA模型能够应用于北京市西城区细菌性痢疾流行趋势的预测,为实施干预措施提供科学依据。
Objective To construct a statistical prediction model suitable for the onset of bacterial dysentery in Xicheng District, Beijing, and to explore the implementation of the quantitative prediction of infectious diseases in this area. Methods SPSS 13.0 statistical software was used to model and fit the ARIMA model of monthly incidence of bacterial dysentery from January 2004 to December 2013 in Xicheng District of Beijing. The model predicts the incidence from January to December 2014 and evaluates the predictive effect of the model. The results of screening the optimal product model ARIMA (1,0,0) (0,1,1) _ (12), BIC = 27.426, the model fitting effect of the measurement Box-Ljung Q difference was not statistically significant (Q = 10.949, P = 0.813), the model residual sequence is white noise. The predicted value of the model fits well with the actual value, and the actual values are all within the 95% confidence interval of the predicted value. Conclusion The ARIMA model can be applied to predict the epidemic trend of bacterial dysentery in Xicheng District of Beijing and provide a scientific basis for the implementation of intervention measures.