Comparison of SARIMA model, Holt-winters model and ETS model in predicting the incidence of foodborne disease
Xiaobing Xian, Liang Wang, Xiaohua Wu, Xiaoqing Tang, Xingpeng Zhai, Rong Yu, Linhan Qu, Mengliang Ye
Abstract
BACKGROUND: According to the World Health Organization, foodborne disease is a significant public health issue. We will choose the best model to predict foodborne disease by comparison, to provide evidence for government policies to prevent foodborne illness. METHODS: The foodborne disease monthly incidence data from June 2017 to April 2022 were obtained from the Chongqing Nan'an District Center for Disease Prevention and Control. Data from June 2017 to June 2021 were used to train the model, and the last 10 months of incidence were used for prediction and validation The incidence was fitted using the seasonal autoregressive integrated moving average (SARIMA) model, Holt-Winters model and Exponential Smoothing (ETS) model. Besides, we used MSE, MAE, RMSE to determine which model fits better. RESULTS: . The MSE, MAE, RMSE of the Holt-Winters model are 8.78, 2.33 and 2.96 respectively, which less than those of the SARIMA and ETS model, and its prediction curve is closer to the true value. The optimal model has good predictive performance. CONCLUSION: Based on the results, Holt-Winters model produces better prediction accuracy of the model.