[Research on the prediction of Hepatitis C incidence trend in Taiyuan City based on combination model].

<b>Objective:</b> Based on the autoregressive integrated moving average (ARIMA) model, back propagation neutral network (BPNN), and ARIMA-BPNN model, select the optimal model suitable for predicting the incidence trend of hepatitis C in Taiyuan City according to the characteristics of the data. <b>Methods:</b> The data of reported cases of hepatitis C in Taiyuan from 2008 to 2021 were selected, and the seasonal trend decomposition chart was used to analyze the seasonal characteristics of the monthly incidence rate of hepatitis C in Taiyuan during the period, and the ARIMA model, BPNN model, and ARIMA-BPNN model were established to predict. The performance of the model was measured using four indicators: mean absolute error (<i>MAE</i>), mean squared error (<i>MSE</i>), root mean square error (<i>RMSE</i>), and mean absolute percentage error (<i>MAPE</i>). <b>Results:</b> A total of 20 025 cases of hepatitis C were reported, and the overall incidence trend was stable. The BPNN model performed well on <i>MSE</i>, <i>MAE,</i> and <i>RMSE</i> indicators, the ARIMA-BPNN model performed well on <i>MAPE</i> indicators, and the ARIMA model performed relatively averagely. <b>Conclusions:</b> The ARIMA-BPNN model is a better model for predicting the trend of hepatitis C in Taiyuan City, with a higher predictive performance than a single model. It has significant prospects in predicting the trend of infectious diseases.