Objective: To explore the application of 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 2.75% and 4.35%. Conclusion: The accurate prediction of infectious diseases is of great significance to the prevention and control of infectious diseases. 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.