梁建国, 冯永亮, 董丽, 范月玲, 高建伟, 王素萍, 董永康. ARIMA乘积季节模型在山西省结核病预测中的应用[J]. 疾病监测, 2023, 38(3): 332-338. DOI: 10.3784/jbjc.202208040342
引用本文: 梁建国, 冯永亮, 董丽, 范月玲, 高建伟, 王素萍, 董永康. ARIMA乘积季节模型在山西省结核病预测中的应用[J]. 疾病监测, 2023, 38(3): 332-338. DOI: 10.3784/jbjc.202208040342
Liang Jianguo, Feng Yongliang, Dong Li, Fan Yueling, Gao Jianwei, Wang Suping, Dong Yongkang. Application of R-based multiple seasonal ARIMA model to predict tuberculosis incidence in Shanxi province[J]. Disease Surveillance, 2023, 38(3): 332-338. DOI: 10.3784/jbjc.202208040342
Citation: Liang Jianguo, Feng Yongliang, Dong Li, Fan Yueling, Gao Jianwei, Wang Suping, Dong Yongkang. Application of R-based multiple seasonal ARIMA model to predict tuberculosis incidence in Shanxi province[J]. Disease Surveillance, 2023, 38(3): 332-338. DOI: 10.3784/jbjc.202208040342

ARIMA乘积季节模型在山西省结核病预测中的应用

Application of R-based multiple seasonal ARIMA model to predict tuberculosis incidence in Shanxi province

  • 摘要:
      目的  应用自回归移动平均(ARIMA)乘积季节模型对山西省2022和2023年结核病发病率进行预测,为结核病防控提供参考依据。
      方法  收集《中国疾病预防控制信息系统-结核病管理信息系统》2010—2021年山西省结核病月发病率数据,进行模型构建和检验。 基于2010—2020年结核病月发病率数据使用R 4.1.0软件构建ARIMA乘积季节模型,并用2021年月发病率检验模型,同时预测山西省2022和2023年结核病流行趋势。
      结果  2010—2021年山西省共报告结核病患者191517例,发病率由68.29/10万下降到23.74/10万,总体呈下降趋势。 每年的1、2、10月发病率较低, 3—6月发病率较高,尤其以冬春交替之际发病率最高。根据2010年1月至2020年12月结核病月发病率拟合出ARIMA(0,1,1)(1,1,1)12模型,该模型的赤迟信息量准则、均方根误差、平均绝对百分比误差和平均绝对误差分别为202.07、0.49、9.19、0.33。 通过检验发现该模型的平均绝对百分比误差为11.34%,预测2022年山西省结核病发病率在0.51/10万~2.12/10万,2023年在0.18/10万~1.81/10万,呈下降趋势。
      结论  ARIMA(0,1,1)(1,1,1)12模型对山西省结核病的预测效果较好,在结核病的防控中具有现实意义。

     

    Abstract:
      Objective  To apply the autoregressive integrated moving average(ARIMA) multiplicative seasonal model in the prediction of tuberculosis (TB) in Shanxi province in 2022 and 2023, and provide reference for TB prevention and control.
      Methods  The monthly incidence data of TB in Shanxi from 2010 to 2021 were collected from China Disease Prevention and Control Information System-Tuberculosis Management Information System. Based on the monthly data of TB incidence in Shanxi from 2010 to 2020, the multiple seasonal ARIMA model was constructed by using R 4.1.0 software , and the model was tested with the monthly incidence data of 2021. Besides, an optimal model was established to predict the incidence trend of TB in Shanxi in 2022 and 2023.
      Results  From 2010 to 2021, a total of 191 517 cases of TB were reported in Shanxi, and the incidence rate dropped from 68.29/100 000 to 23.74/100 000, showing an overall downward trend. The incidence was lower in January, February and October and higher from March to June, especially in the late winter and early spring, the incidence was highest. Based on the monthly incidence of TB from January 2010 to December 2020, the ARIMA (0,1,1) (1,1,1)12 model was fitted, and AIC, RMSE, MAPE and MAE of the model were 202.07, 0.49, 9.19, and 0.33, respectively. The testing results suggested that the average absolute error percentage of the model was 11.34%, the incidence of TB in Shanxi was predicted to be (0.51−2.12)/100 000 in 2022 and (0.18−1.81)/100 000 in 2023.
      Conclusion  ARIMA (0,1,1) (1,1,1)12 model has a good prediction power on TB in Shanxi, which has practical significance in the prevention and control of TB.

     

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