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      Application of SARIMA model in the prediction of tuberculosis incidence in Suzhou

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          Abstract

          Objective To establish a SARIMA model and predict the incidence of tuberculosis in Suzhou, and we provide reference for prevention and control of tuberculosis in Suzhou.

          Methods The monthly incidence of tuberculosis in Suzhou was collected from January 2010 to December 2018 in tuberculosis information management system (new). Through time-series analysis, a SARIMA model was established to predict the incidence of tuberculosis in Suzhou in 2019.

          Results The incidence of tuberculosis in Suzhou is of distinct seasonality. The peak month is May, and the trough is February. Best fitting model for the incidence of tuberculosis in Suzhou is SARIMA(0,1,1)×(0,1,1) 12, AIC=9.590, SBC=9.644. Model parameters are statistically significant, and model residual is white noise. Mean absolute percentage error (MAPE) between predictive and actual values is 7.943%. The model is of high prediction accuracy. It is predicted that the number of tuberculosis cases in Suzhou will be 3 467 in 2019, and the average number of monthly incidence is 289. The incidence level of 2019 is slightly lower than 2018.

          Conclusions SARIMA(0,1,1)×(0,1,1) 12 model exactly fitted the changes in the number of tuberculosis cases in Suzhou over time, and can be used for short-term prediction of the monthly incidence of tuberculosis in Suzhou.

          Abstract

          摘要: 目的 建立苏州市肺结核发病的 SARIMA 模型并预测发病,为苏州市肺结核防控提供参考。 方法 收集结 核病信息管理系统 (新) 中苏州市 2010 年 1 月—2018 年 12 月肺结核月发病数, 通过时间序列分析建立 SARIMA 模型并 预测苏州市 2019 年肺结核的发病情况。 结果 苏州市肺结核发病数具有明显的季节周期性, 每年的发病最高峰为 5 月, 发病最低谷为 2 月。苏州市肺结核发病数的最佳拟合模型为 SARIMA (0,1,1)×(0,1,1) 12, AIC=9.590, SBC=9.644, 模型 参数均具有统计学意义, 模型残差为白噪声序列, 模型的预测值与实际值平均绝对百分比误差 MAPE=7.943%,模型预 测精度较高。预测苏州市 2019 年肺结核发病数为 3 467 例, 月发病数平均值为 289 例, 发病水平较 2018 年略有下降。 结论 SARIMA(0,1,1)×(0,1,1) 12 模型能较好拟合出苏州市肺结核发病数的时间变化趋势, 可应用于苏州市肺结核月发病 数的短期预测。

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          Author and article information

          Journal
          CTM
          China Tropical Medicine
          China Tropical Medicine (China )
          1009-9727
          1 April 2020
          1 May 2020
          : 20
          : 4
          : 339-342
          Affiliations
          1Department of Tuberculosis Control and Prevention, Suzhou Center for Disease Control and Prevention, Suzhou, Jiangsu 215004, China
          Author notes
          Corresponding author: ZHANG Xiaolong, E-mail: gsdx_zxl@ 123456163.com
          Article
          j.cnki.46-1064/r.2020.04.09
          10.13604/j.cnki.46-1064/r.2020.04.09
          © 2020 Editorial Department of China Tropical Medicine

          This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 Unported License (CC BY-NC 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See https://creativecommons.org/licenses/by-nc/4.0/.

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