JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES) ›› 2016, Vol. 54 ›› Issue (9): 82-86.doi: 10.6040/j.issn.1671-7554.0.2015.1163

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Application of SARIMA model in predicting the incidence of mumps

LI Runzi1, ZHANG Tao1, LIANG Yumin 2, LUO Cheng1, JIANG Zheng1, XUE Fuzhong1, LIU Yanxun1, LIU Jing1, LI Xiujun1   

  1. 1. Department of Biostatistics, School of Public Health, Shandong University, Jinan 250012, Shandong, China;
    2. Center for Disease Control and Prevention of Jining City, Jining 272000, Shandong, China
  • Received:2015-11-24 Online:2016-09-10 Published:2016-09-10

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Abstract: Objective To predict the incidence of mumps with autoregressive integrated moving average(SARIMA)model so as to provide scientific guidance for its prevention and control. Methods Time-series data of monthly mumps cases from Jan. 2009 to July 2013 were analyzed using SARIMA model and predictive model was established to predict the incidence from August to December 2013. Results From 2009 to 2013, a total of 8,520 cases of mumps were reported in Jining City. Eventually the optimal model of SARIMA(0,1,1)(0,1,1)12 was established, and the information criterion(AIC)was 74.45. Parameters estimated were statistically significant, and residuals were white noise sequence. Monthly mumps cases from January 2009 to July 2013 were used for model fitting and the monthly mumps cases from Aug. to Dec. 2013 predicted by the optimal model were within the 95% confidence interval, and were consistent with the trend of the actual incidence, which demonstrated the rationality of the model. Correlation between actual case number and fitted case number was statistically significant(r=0.75, P<0.000 1). Conclusion SARIMA model can fit the incidence of dynamic change of mumps, and can be used to make short-term prediction and to provide scientific evidence for the prevention and control of mumps.

Key words: Time series analysis, Seasonal autoregressive integrated moving average model, Prediction, Mumps

CLC Number: 

  • R181.25
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