ARIMA乘积季节模型在山东省肺结核发病预测中的应用

doi:10.6040/j.issn.1671-7554.0.2021.0049

摘要/Abstract

摘要： 目的根据山东省肺结核的季节性、趋势性建立求和自回归移动平均(ARIMA)乘积季节模型,预测山东省肺结核发病趋势,调整防控措施。方法应用R软件对2010年1月至2019年12月山东省肺结核传染病疫情月度数据建立最优模型,预测2020年1月至10月肺结核发病数,并与实际值进行比较,以此评估模型的预测效果,预测2020年11月至2021年12月的发病趋势。结果山东省肺结核发病数表现为年度周期性,最优模型为ARIMA(3,1,0)(0,1,1)₁₂,2010年1月至2019年12月拟合结果准确性显示平均绝对百分比误差仅为5.50%, 2020年1月至10月模型预测效果的平均相对百分比误差为21.69%,2020年11月至2021年12月的发病数较同期有轻微变化。结论 ARIMA乘积季节模型能够较好地对山东省肺结核发病趋势进行拟合及预测。

关键词: 肺结核, 时间序列, ARIMA模型, 季节性, 预测

Abstract: Objective According to the seasonality and trend of pulmonary tuberculosis in Shandong Province, to establish an Autoregressive Integrated Moving Average(ARIMA)product seasonal model, predict the incidence of pulmonary tuberculosis in Shandong Province and adjust prevention and control measures. Methods An optimal model for the monthly data of pulmonary tuberculosis infectious diseases in Shandong Province from January 2010 to December 2019 was established using R software. The number of pulmonary tuberculosis cases from January to October 2020 was predicted and compared with the actual value to evaluate the prediction effect of the model. Further, the incidence trend of pulmonary tuberculosis cases from November 2020 to December 2021 was predicted. Results The number of pulmonary tuberculosis cases in Shandong Province showed an annual cycle, and the optimal model is ARIMA(3,1,0)(0,1,1)₁₂. The accuracy of fitting results from January 2010 to December 2019 showed that the mean absolute percentage error was only 5.50%. The mean absolute percentage error of the model prediction from January to October 2020 was 21.69%. Compared with the same period, there was a slight change in the number of cases from November 2020 to December 2021. Conclusion The ARIMA product seasonal model can rather satisfactorily fit and predict the incidence of tuberculosis in Shandong Province.

Key words: Tuberculosis, Time series, ARIMA model, Seasonal, Predict

中图分类号:

R183

田庆,刘永鹏,张晶晶,刘洪庆. ARIMA乘积季节模型在山东省肺结核发病预测中的应用[J]. 山东大学学报 (医学版), 2021, 59(7): 112-118.

TIAN Qing, LIU Yongpeng, ZHANG Jingjing, LIU Hongqing. Application of ARIMA multiplicative seasonal model in the prediction of pulmonary tuberculosis incidence in Shandong Province[J]. Journal of Shandong University (Health Sciences), 2021, 59(7): 112-118.

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