Probabilistic forecasting of hand, foot and mouth disease in Mainland China using Bayesian additive regression tree model.

ABSTRACT: Hand, foot, and mouth disease (HFMD) is a serious public health concern in China. Accurately forecasting HFMD and providing forecast uncertainty is significant for decision making by public health workers. However, existing studies have mainly focused on the accuracy of point predictions, with limited research using probabilistic predictions to provide uncertainty. In this study, we used Bayesian additive regression tree probabilistic model for point forecasting and providing forecasting intervals and compared the performance with ARIMA model based on the monthly number of HFMD cases in seven regions of mainland China from June 2008 to December 2018. Compared with ARIMA model, the mean values of MAPE and RMSE of BART model were 42.463 and 4124.997, which decreased by 73.465% and 16.332%, a

SUBMITTER: Geng X 

PROVIDER: S-EPMC12484543 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature