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张珍, 刘星言, 李言言, 邢莹莹, 王永斌, 胡斌. 基于贝叶斯结构时间序列模型评估我国梅毒流行趋势[J]. 疾病监测, 2023, 38(9): 1087-1093. DOI: 10.3784/jbjc.202211030474
引用本文: 张珍, 刘星言, 李言言, 邢莹莹, 王永斌, 胡斌. 基于贝叶斯结构时间序列模型评估我国梅毒流行趋势[J]. 疾病监测, 2023, 38(9): 1087-1093. DOI: 10.3784/jbjc.202211030474
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Zhang Zhen, Liu Xingyan, Li Yanyan, Xing Yingying, Wang Yongbin, Hu Bin. Estimated prevalence of syphilis in China based on Bayesian structural time series model[J]. Disease Surveillance, 2023, 38(9): 1087-1093. DOI: 10.3784/jbjc.202211030474
Citation: Zhang Zhen, Liu Xingyan, Li Yanyan, Xing Yingying, Wang Yongbin, Hu Bin. Estimated prevalence of syphilis in China based on Bayesian structural time series model[J]. Disease Surveillance, 2023, 38(9): 1087-1093. DOI: 10.3784/jbjc.202211030474
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基于贝叶斯结构时间序列模型评估我国梅毒流行趋势

Estimated prevalence of syphilis in China based on Bayesian structural time series model

    摘要
  • 摘要:
      目的  探讨贝叶斯结构时间序列（BSTS）模型在预测我国梅毒流行趋势中的应用价值。
      方法  收集2005年1月至2022年8月我国梅毒发病数据，采用Eviews10软件解析梅毒月发病数据中的趋势和季节组分；采用RStudio软件构建模型，其中2005年1月至2021年12月的数据作为训练集拟合BSTS模型，2022年1—8月数据作为测试集验证模型的预测效果，并将其预测准确性与求和自回归滑动平均混合（ARIMA）模型进行比较。 所有统计学分析检验水准指定为 \alpha ＝0.05。
      结果  我国梅毒发病总体呈上升态势，具有周期性和季节性，每年1—2月为低谷，7—8月为高峰。 在训练和测试集上，BSTS模型产生的平均绝对百分比误差（分别为4.95%和5.73%）均小于ARIMA模型（分别为5.44%和6.52%）；同样也发现，BSTS模型产生的平均绝对误差、均方根误差和均方根百分比误差均小于ARIMA模型。 稳健性结果表明了同样的结果。 基于BSTS模型预测的2022年9月至2023年12月我国梅毒发病总数为719 600［95%置信区间（CI）：605 295～826 086］例，月均发病数为44 975（95%CI：37 831～51 631）例。
      结论  我国梅毒是一种季节性疾病，发病仍处于高水平；BSTS模型能准确评估我国梅毒动态流行趋势，可为梅毒精准防控提供技术支撑。

     

    Abstract:
      Objective  To evaluate the performance of Bayesian structural time series (BSTS) model for estimating the prevalence of syphilis in China.
      Methods  The incidence data of syphilis in China from January 2005 to August 2022 were collected. The trend and seasonal components in the syphilis monthly incidence data were analyzed by using software Eviews10. The model was constructed by using software RStudio, and in the model development, the incidence data from January 2005 to December 2021 were used as the training set to fit the BSTS model, whereas the incidence data from January to August 2022 were used as the test set to verify the prediction potential of the model. Subsequently, the prediction accuracy of BSTS model was compared with that of autoregressive integrated moving average (ARIMA) model. The test levels for all statistical analyses were designated as \alpha =0.05.
      Results  Overall, the incidence of syphilis in China showed an upward trend and had a periodicity and seasonality with the trough during January-February and the peak during July-August. On the training and testing sets, the average absolute percentage error of BSTS model (4.95%, 5.73%) was lower than those of ARIMA model (5.44%, 6.52%). Also, it was found that the mean absolute error, root mean square error, and root mean square percentage error of BSTS model were lower than those of ARIMA model. The robustness test indicated the same result. The predicted total case number of syphilis was 719 600 (95%CI: 605 295–826 086) from September 2022 to December 2023 by BSTS model, with a monthly average of 44 975 cases (95%CI: 37 831–51 631).
      Conclusion  In China, syphilis is a seasonal disease with high incidence. The BSTS model can be used for accurately assessing the incidence of syphilis and providing technical support for the accurate prevention and control of syphilis.

     

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