Prediction of influenza in Chongqing，China，based on the Autoregressive Integrated Moving Average model

Abstract:

Objective To investigate the trend of influenza prevalence by constructing an Autoregressive Integrated Moving Average （ARIMA） model for influenza and making predictions on the validation set，and to provide a scientific basis for the prevention and control of influenza in Chongqing，China.Methods In this study，R software was used for the ARIMA model fitting of influenza data in Chongqing from January 2010 to June 2021，and the data from July to December 2021 were used to evaluate the fitting performance of the model.Results The prevalence of this influenza disease presented with a noticeable seasonal pattern，with a yearly cycle and a peak in winter and spring. The overall prevalence rate tended to increase first and then decrease，and the best-fitting model was ARIMA（0，1，2）×（0，1，2）₁₂，which had a root mean square error of 10.70 and a mean absolute percentage error of 70.04% in predicting the attack rate in July to December 2021，suggesting that the model had good predictive efficacy.Conclusion The ARIMA model has a certain effect in predicting the onset and prevalence trend of influenza in Chongqing and can estimate the attack rate of influenza in the future，which can provide a reference for the prevention and control of influenza in the future.