ARIMA模型和季节指数模型在湖北省流行性腮腺炎发病预测中比较

Comparativestudy of ARIMA model and seasonal index model in the prediction of mumps in Hubei Province

目的采用ARIMA模型和季节指数模型对流行性腮腺炎发病趋势进行预测,比较模型的优劣,为流行性腮腺炎防控提供一种科学的预测预警方法。方法基于2008—2019年湖北省流行性腮腺炎月发病率数据,分别建立ARIMA模型和季节指数模型。结果2008—2019年年均发病率28.89/10万;4~7月为高发月份;建立的ARIMA模型和季节指数模型分别为(1-1.070B+0.441B^2-0.291B^3)*(1-B 12)*Xt=(1-0.611B^12)*εt、X t=(2.802-0.006t)*S t;ARIMA模型和季节指数模型的平均相对误差分别为11.49%、20.86%。结论ARIMA模型和季节指数模型在流行性腮腺炎发病时间特征和趋势预测上均有较好的适用性;ARIMA模型在拟合年度变化趋势上更有优势,季节指数模型在拟合月度变化趋势上也具有参考性,可综合两种模型一起用于流行性腮腺炎发病趋势的预测。

Objective To establish an ARIMA model and a seasonal index model to predict the trend of mumps,compare the advantages and disadvantages of the two models,and to provide a scientific basis for the prevention and control of mumps.Methods ARIMA model and seasonal index model were established based on the monthly incidence of mumps in Hubei Province from 2008 to 2019.Results The average annual incidence rate from 2008 to 2019 was 28.89/100,000.April-July was the month of high incidence.The established ARIMA model and seasonal index model were(1-1.070B+0.441B 2-0.291B^3)*(1-B^12)*X t=(1-0.611B^12)*t and X t=(2.802-0.006t)*S t.The average relative errors of the ARIMA model and the seasonal index model were 11.49% and 20.86%,respectively.Conclusion The ARIMA model and the seasonal index model both have good applicability in predicting the onset time characteristics and trend of mumps.However,while the ARIMA model demonstrated more advantages in fitting the annual change trend,the seasonal index model is better in fitting the monthly change trend.The two models can be used in combination to predict the trend of mumps.