Epidemiologic characteristics and prediction of incidence trend of all types of influenza based on ARIMA model

  Objective  To analyze the epidemiologic characteristics and distribution of influenza in China from 2010 to 2019, and predict the incidence trends of all types of influenza.

  Methods  Seasonal ARIMA model was used for original series pre-process, model identification, parameters estimation and statistical modeling to predict the incidence trend of influenza.

  Results  The influenza time series model constructed was ARIMA (1,2,1) (0,1,1)₁₂, and the data information was fully extracted (Q=14.257, P>0.05), the relative error was about 10%. Influenza A prediction model was ARIMA (2,1,1) (0,2,2)₁₂, the data information was fully extracted (Q=13.236, P>0.05). The predicted incidence of influenza A was high from December 2018 to March 2019, and the incidence decreased rapidly from April, similar to the actual situation. Relative error was controlled within 10%; The influenza B prediction model was ARIMA (1,2,1) (1,0,1)₁₂, and the data information was fully extracted (Q=9.841, P>0.05), but the incidence of influenza B in 2019 predicted by the model was low and the relative error was high.

  Conclusion  Influenza and influenza A seasonal ARIMA models had better prediction effects. The data information of influenza B prediction model was fully extracted, but the relative error was high, which might be related to the absence of obvious long-term trend of influenza B incidence.