Zhang Fengquan, Li Yanyan, Li Xinxiao, Zhang Bingjie, Xue Chenlu, Wang Yongbin
Center for Experimental Teaching, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, People's Republic of China.
Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, People's Republic of China.
Infect Drug Resist. 2024 Dec 20;17:5745-5754. doi: 10.2147/IDR.S462998. eCollection 2024.
This study sets out to explore the forecasting value in syphilis incidence of the Bayesian structural time series (BSTS) model in Jiangsu Province.
The seasonal autoregressive integrated moving average (ARIMA) and BSTS models were constructed using the series from January 2017 to December 2021, and the prediction accuracy of both models was tested using the series from January 2022 to November 2022.
From January 2017 to November 2022, the total number of syphilis cases in Jiangsu Province was 170629, with an average monthly notification cases of 2403. The optimal model was ARIMA (1,0,0) (0,1,1) 12 (AIC = 663.12, AICc = 664.05, and BIC = 670.60). The model coefficients were further tested: AR1 = 0.48 (t = 3.46, P < 0.001), and SMA1 =-0.48 (t =-2.32, P = 0.01). The mean absolute deviation, mean absolute percentage error, root mean square error, and root mean square percentage error from the BSTS model were smaller than those from the ARIMA model. The total number of syphilis cases predicted by the BSTS model from December 2022 to December 2023 in Jiangsu Province was 29902 (95% CI: 16553 ~ 42,401), with a monthly average of 2300 (95% CI: 1273 ~ 3262) cases.
Syphilis is a seasonal disease in Jiangsu Province, and its incidence is still at a high level. The BSTS model is superior to the ARIMA model in dynamically predicting the incidence trend of syphilis in Jiangsu Province and has better application value.
本研究旨在探讨贝叶斯结构时间序列（BSTS）模型对江苏省梅毒发病率的预测价值。
利用2017年1月至2021年12月的序列构建季节性自回归积分滑动平均（ARIMA）模型和BSTS模型，并使用2022年1月至2022年11月的序列检验两种模型的预测准确性。
2017年1月至2022年11月，江苏省梅毒病例总数为170629例，月均报告病例数为2403例。最优模型为ARIMA(1,0,0)(0,1,1)12（AIC = 663.12，AICc = 664.05，BIC = 670.60）。对模型系数进一步检验：AR1 = 0.48（t = 3.46，P < 0.001），SMA1 = -0.48（t = -2.32，P = 0.01）。BSTS模型的平均绝对偏差、平均绝对百分比误差、均方根误差和均方根百分比误差均小于ARIMA模型。BSTS模型预测江苏省2022年12月至2023年12月梅毒病例总数为29902例（95%CI：16553～42401），月均2300例（95%CI：1273～3262）。
梅毒在江苏省为季节性疾病，发病率仍处于较高水平。BSTS模型在动态预测江苏省梅毒发病趋势方面优于ARIMA模型，具有较好的应用价值。
