Objective：To explore the application of autoregressive integrated moving average（ARIMA）model based on paired test in predicting the incidence of hepatitis A in China，and put forward a new idea and method for evaluating the prediction effect of time series model. Methods：An ARIMA model was established for the monthly incidence of hepatitis A infectious diseases in China from January 2004 to December 2021，and the monthly incidence of hepatitis A infectious diseases from January to August 2022 was predicted. The prediction effect of the model was evaluated by paired t-test and error analysis. Results：The results of paired t-test showed that there was no significant difference between the monthly incidence of hepatitis A predicted by ARIMA（1，1， 0）（0，1，1）₁₂ model and the actual monthly incidence of hepatitis A（P ＞ 0.05），indicating that the model had good prediction ability，and the mean relative error and standard deviation of the prediction results were 3.86% and 3.25%. Conclusion：ARIMA product season model can accurately predict the incidence trend of hepatitis A in China. The paired test provides an objective basis for evaluating the prediction effect of time series model，and solves the problem of evaluating the prediction effect of time series model well.