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87 and 2.98, the fitting accuracy indexes, such as RMSE, MAE and MAPE were 0.98, 0.77 and 5.8 respectively; the prediction accuracy indexes, such as RMSE, MAE and MAPE were 0.62, 0.45 and 3.77, respectively. Based on the SARIMA((2),0,(2))(0,1,12 model, we predicted the TB incidence in Guangxi from July 2019 to December 2020. CONCLUSIONS This study filled the gap in the prediction of TB incidence in Guangxi in recent years. The established SARIMA((2),0,(2))(0,1,12 model has high prediction accuracy and good prediction performance. The r
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