原梅, 张治国, 豆智慧, 王路钦, 张峣, 李卫民, 高基民. 北京市昌平区肺结核发病数ARIMA模型预测[J]. 疾病监测, 2015, 30(12): 1045-1049. DOI: 10.3784/j.issn.1003-9961.2015.12.014
引用本文: 原梅, 张治国, 豆智慧, 王路钦, 张峣, 李卫民, 高基民. 北京市昌平区肺结核发病数ARIMA模型预测[J]. 疾病监测, 2015, 30(12): 1045-1049. DOI: 10.3784/j.issn.1003-9961.2015.12.014
YUAN Mei, ZHANG Zhi-guo, DOU Zhi-hui, WANG Lu-qin, ZHANG Yao, LI Wei-min, GAO Ji-min. Application of ARIMA model in predicting incidence of pulmonary tuberculosis in Changping district, Beijing[J]. Disease Surveillance, 2015, 30(12): 1045-1049. DOI: 10.3784/j.issn.1003-9961.2015.12.014
Citation: YUAN Mei, ZHANG Zhi-guo, DOU Zhi-hui, WANG Lu-qin, ZHANG Yao, LI Wei-min, GAO Ji-min. Application of ARIMA model in predicting incidence of pulmonary tuberculosis in Changping district, Beijing[J]. Disease Surveillance, 2015, 30(12): 1045-1049. DOI: 10.3784/j.issn.1003-9961.2015.12.014

北京市昌平区肺结核发病数ARIMA模型预测

Application of ARIMA model in predicting incidence of pulmonary tuberculosis in Changping district, Beijing

  • 摘要: 目的 探讨自回归滑动平均混合模型(autoregressive integrated moving average model, ARIMA)模型在北京市昌平区肺结核发病数预测中的应用,阐述建模过程并预测2015年昌平区肺结核发病数,为制定防治策略合理配置资源等提供参考。方法 采用全国结核病网络专报系统中2009-2014年现住址为北京市昌平区的肺结核报告发病数数据,通过模型识别、参数估计、检验诊断及模型评价,建立昌平区结核病发病数的ARIMA模型,并预测其2015年肺结核发病数。结果 现住址为昌平区的肺结核发病数预测模型为ARIMA(0,1,1)(0,1,1)12,预测2015年的新发报告肺结核患者总数为851例,模型2015年第一、二季度(1-6月)预测误差率为1.65%,不到10%,模型预测精度较好。结论 ARIMA模型适用于昌平区肺结核发病数的早期预测。

     

    Abstract: Objective To establish an ARIMA model for the prediction of incidence of pulmonary tuberculosis(TB) in Changping district, Beijing in 2015 and provide evidence for the prevention and control of TB and resource allocation. Methods The incidence data of TB in local population in Changping during 2009-2014 were collected from the National Tuberculosis Information Management System. An ARIMA model was established by means of model identification, parameter estimation, detection/diagnosis and model evaluation. The incidence of TB in Changping in 2015 was predicted. Results With the established model of ARIMA(0,1,1)(0,1,1)12, it was predicted that the pulmonary TB case number would be 851 in local population in Changping in 2013. The error rate of the prediction during January-June 2015 was 1.65%, lower than 10%, indicating the high precision of the model. Conclusion This study showed that the ARIMA model is applicable for the prediction of TB incidence in Changping.

     

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