Journal of Capital Medical University ›› 2019, Vol. 40 ›› Issue (2): 286-291.doi: 10.3969/j.issn.1006-7795.2019.02.024

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Application of autoregressive integrated moving average model on monitoring influenza-like illness(ILI) case in hospital

Li Guiqin1, Huang Liyong2, Qin Fengzhi3   

  1. 1. Office for Disease Prevention and Control, Chaoyang Hospital, Capital Medical University, Beijing 100020, China;
    2. Department of Infectious Disease and Endemic Disease Prevention, Chaoyang Centers For Disease Control and Prevention, Beijing 100021, China;
    3. College of Public Health, Xiamen University, Xiamen 361102, Fujian Province, China
  • Received:2018-11-20 Online:2019-03-21 Published:2019-04-15

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Abstract: Objective To analyze the influenza-like illness (ILI) cases data reported via autoregressive integrated moving average model (ARIMA) model, and to explore the effect of the model on ILI case warning, to carry out the influenza prevention work comprehensively, and to deal with the epidemic situation efficiently.Methods The ARIMA model was established via the ILI cases data reported by Chaoyang Hospital, Capital Medical University from January 12, 2014 to October 14, 2017, and data from October 15 to December 24, 2017 was selected as the test set to evaluate predictive effect. Results The coefficient of determination (R2) of the ARIMA (2,0,0) model is 0.87. The predicted values accord well with actual values.Conclusion The model analysis of ARIMA (2,0,0) shows that it has a good early warning effect in influenza surveillance in Chaoyang Hospital, Capital Medical University. This model can provide reference for other medical institutions in monitoring ILI cases.

Key words: influenza-like illness cases, monitor, autoregressive integrated moving average model

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