Application of autoregressive integrated moving average model in predicting the reported notifiable communicable diseases in China

VernacularTitle:ARIMA模型在我国法定传染病报告数中的应用
Author: Zhongzhou SHEN ¹ ; Shuai MA ; Yimin QU ; Yu JIANG
Author Information

1. 100730,北京协和医学院公共卫生学院
Keywords: Notifiable disease; Autoregressive integrated moving average; Prediction
From: Chinese Journal of Epidemiology 2017;38(12):1708-1712
CountryChina
Language:Chinese
Abstract: Objective To develop the models for predicting the reported legally notifiable diseases in China.Autoregressive integrated moving average (ARIMA) model was applied to forecast the trend of diseases.Methods Cases used for building the model were from of the records of Notifiable Infectious Diseases in China from May 2009 to July 2016 with R software and the model's predictive ability was tested by the data from August 2016 to January 2017.Results A strong seasonal nature was seen in the reported cases of notifiable communicable diseases,with the lowest point in February and highest peak in June.ARIMA (4,1,0) (1,1,1)12 model was established by the team to forecast the notifiable communicable diseases.Data showed that the biggest and lowest relative errors appeared as 9.78％ and 2.21％,respectively,with the mean of the relative error as 5.39％.Conclusion Based on the results of this study,the ARIMA (4,1,0) (1,1,1)12 model seemed to have had the sound prediction of notifiable communicable diseases in China.