Establishment and prediction of multiple seasonal ARIMA model for other infectious diarrhea in Shangcheng District
XU Ling1,2, LI Xiu-yang1
1. Department of Epidemiology and Biostatistics, Center for Clinical Big Data & Statistics, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China; 2. Shangcheng District Center for Disease Control and Prevention, Hangzhou, Zhejiang 310043, China
Abstract：Objective To establish the multiple seasonal auto-regressive integrated moving average (ARIMA) model for other infectious diarrhea diseases in Shangcheng District, and to provide references for the early prevention and control. Methods SPSS 25.0 software was used to establish the multiple seasonal ARIMA model based on the data about the incidence of other infectious diarrhea diseases in Shangcheng District from 2010 to 2020. The fitting effect of the model was evaluated based on regression prediction on the number of monthly incidence in 2021, and the established model was used to predict the number of monthly incidence in 2022. Results A total of 40,534 cases of other infectious diarrhea diseases were reported in Shangcheng District from 2010 to 2020, with an average annual reported incidence of 3,685 cases. No death case was reported. The optimal model established was ARIMA (2,1,1) (1,1,1)12, with stable R2=0.870, Bayesian information criterion (BIC)=9.524, mean absolute percentage error (MAPE)=27.351. No statistical significance was found in Box-Ljung test (Q=10.420, P=0.659). The measured incidence trend of the model was basically consistent with the predicted incidence trend, and the average relative error between the predicted value and the measured value was 23.88%, indicating a good prediction effect. ARIMA (2,1,1) (1,1,1)12 model was employed to predict the incidence of other infectious diarrhea diseases in Shangcheng District in 2022. The predicted values were all within the 95% confidence limit, and there were two peaks of incidence in summer and winter, which wereconsistent with the monitoring data of Zhejiang Province and the whole country. Conclusion ARIMA (2,1,1) (1,1,1)12 model can make a good prediction for other infectious diarrhea diseases in Shangcheng District, and plays a certain role in early prevention and control.
徐玲, 李秀央. 上城区其他感染性腹泻ARIMA乘积季节模型的建立与预测[J]. 实用预防医学, 2023, 30(1): 111-115.
XU Ling, LI Xiu-yang. Establishment and prediction of multiple seasonal ARIMA model for other infectious diarrhea in Shangcheng District. , 2023, 30(1): 111-115.
2023, Vol. 30 
