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ARIMA model of data of hepatitis C report of China from 2004 to 2012 and trend prediction

WU Tian-yong1, ZENG Qing1, YU Meng2, LIU Shi-wei2, LI Qin3, ZHAO Han3   

  1. 1.Department of Biostatistics， School of Public Health， Chongqing Medical University， Chongqing 400016， China; 2.Chinese Center for Disease Control and Prevention， Beijing 102200， China； 3.Chongqing Center for Disease Control and Prevention， Chongqing 400042， China
  • Online:2014-05-28 Published:2014-05-30

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Abstract:

Objective To analyze, fit, and forecast the data of hepatitis C report of China by the autoregressive integrated moving average model (ARIMA). Methods The data of hepatitis C report of China from January, 2004 to July, 2012 was differentiated to obtain smoothness and analysis, fitting, and forecasting were conducted by the seasonal ARIMA model. Results The incidence of Hepatitis C showed an increasing trend from January, 2004 to July, 2012 and has obvious periodic changes on a basis of one year. The smoothing test, differentiation, and model identification and diagnosis were conducted based on the data of Hepatitis C report and the obtained optimal model was seasonal series of ARIMA (1,1,1)×(1,1,1)12. The residual test of this model showed a white noise sequence, fitting the data in the 95% confidence interval. Based on the cases of hepatitis C from July, 2012 to December, 2014, it could be predicted that the incidence of hepatitis C increased continuously and showed an obvious trend of periodical fluctuation. Conclusion The seasonal series ARIMA model of time series can simulate and predict the tendency of incidence of hepatitis C in China and can provide reference for the prevention and control of the epidemic.

Key words: time series, hepatitis C, seasonal ARIMA model of seasonal, forecast