Department of Respiratory, Children's Hospital of Chongqing Medical University, Chongqing, 40010, People's Republic of China.
College of Stomatology, Chongqing Medical University, 40016, Chongqing, People's Republic of China.
Interdiscip Sci. 2019 Mar;11(1):77-85. doi: 10.1007/s12539-019-00318-x. Epub 2019 Feb 8.
Tuberculosis (TB) is a global infectious disease and one of the ten leading causes of death worldwide. As TB incidence is seasonal, a reliable forecasting model that incorporates both seasonal and trend effects would be useful to improve the prevention and control of TB. In this study, the X12 autoregressive integrated moving average (X12-ARIMA) model was constructed by dividing the sequence into season term and trend term to forecast the two terms, respectively. Data regarding the TB report rate from January 2004 to December 2015 were included in the model, and the TB report data from January 2016 to December 2016 were used to validate the results. The X12-ARIMA model was compared with the seasonal autoregressive integrated moving average (SARIMA) model. A total of 383,797 cases were reported from January 2004 to December 2016 in Chongqing, China. The report rate of TB was highest in 2005 (151.06 per 100,000 population) and lowest in 2016 (72.58 per 100,000 population). The final X12-ARIMA model included the ARIMA (3,1,3) model for the trend term and the ARIMA (2,1,3) model for the season term. The SARIMA (1,0,2) * (1,1,1) model was selected for the SARIMA model. The mean absolute error (MAE) and mean absolute percentage error (MAPE) of fitting and predicting performance based on the X12-ARIMA model were less than the SARIMA model. In conclusion, the occurrence of TB in Chongqing is controlled, which may be attributed to socioeconomic developments and improved TB prevention and control services. Applying the X12-ARIMA model is an effective method to forecast and analyze the trend and seasonality of TB.
结核病（TB）是一种全球性传染病，也是全球十大死亡原因之一。由于结核病的发病具有季节性，因此建立一个同时考虑季节性和趋势性的可靠预测模型，将有助于改善结核病的预防和控制。本研究通过将序列划分为季节项和趋势项来分别预测这两个项，构建了 X12 自回归积分移动平均（X12-ARIMA）模型。纳入模型的数据为 2004 年 1 月至 2015 年 12 月的结核病报告率，用 2016 年 1 月至 12 月的结核病报告数据进行验证。并将 X12-ARIMA 模型与季节性自回归积分移动平均（SARIMA）模型进行了比较。2004 年 1 月至 2016 年 12 月期间，重庆市共报告结核病病例 383797 例。重庆市结核病报告发病率在 2005 年（151.06/10 万）最高，在 2016 年（72.58/10 万）最低。最终 X12-ARIMA 模型的趋势项包含 ARIMA（3,1,3）模型，季节项包含 ARIMA（2,1,3）模型。SARIMA 模型选择 SARIMA（1,0,2）*（1,1,1）模型。基于 X12-ARIMA 模型的拟合和预测性能的平均绝对误差（MAE）和平均绝对百分比误差（MAPE）均小于 SARIMA 模型。综上所述，重庆市结核病发病得到控制，这可能归因于社会经济的发展和结核病防治服务的改善。应用 X12-ARIMA 模型是一种有效的方法，可用于预测和分析结核病的趋势和季节性。
