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福建省介水传染病发病短期定量预测研究 [中文引用][英文引用]

Quantitative Prediction on Short-term Incidence of Waterborne Diseases in Fujian

作者(英文):ZHU Hansong  OU Jianming  XIE Zhonghang  WU Shenggen  LIN Jiawei  HUANG Wenlong 
单位(英文): 
关键词(英文):ARIMA  waterborne infectious disease  prediction  quantification  short-term 
分类号:R12
出版年·卷·期(页码):2019·9·第6期(568-571,576)
DOI:
-----摘要:-------------------------------------------------------------------------------------------

目的 采用时间序列模型(ARIMA)对福建省介水传染病发病数进行短期定量预测,为风险评估提供数据。方法 运用R 3.4.3软件基于ARIMA模型对福建省2004年1月—2018年4月介水传染病月发病数进行分析和建模,并对2018年5—12月进行短期预测。结果 2004年1月—2018年4月福建省介水传染病报告发病数共409 042例,呈上升趋势和周期性波动。季节效应比较明显,秋冬季节出现发病高峰,其中12月份较上月增长了29.31%。ARIMA(2,1,1)(2,1,2)12为最佳拟合模型,预测值和实际值吻合较好,准确度较高,各准确性度量值分别为:ME(-0.02)、RMSE(0.19),MAE(0.13)、MPE(-0.32%)、MAPE(1.70)、MASE(0.69)。2018年5—9月的实际发病数与预测值相比,绝对误差均值和相对误差分别为-203例和-8.62%。2018年10—12月预测值分别为2401例、2 130例和3 643例。结论 ARIMA模型能够对福建省介水传染病发病数进行较准确的短期预测,可为风险评估和制定防控措施提供数据基础。
 

-----英文摘要:---------------------------------------------------------------------------------------

Objectives The time series model (ARIMA) was used to conduct short-term quantitative predictions of the incidence of waterborne infectious diseases in Fujian Province, providing a reliable data basis for risk assessment. Methods Based on the ARIMA model, the R 3.4.3 software was used to analyze the monthly incidence of waterborne infectious diseases and establish the model from January 2004 to April 2018 in Fujian Province, and then to conduct short-term predictions in May-December 2018. Results From January 2004 to April 2008, the number of reported cases of waterborne infectious diseases in Fujian Province was 409 042, showing an upward trend and cyclical fluctuations. The seasonal effect was more obvious, and the incidence peaks appear in autumn and winter, among them, December increased by 29.31% over the previous month. ARIMA(2,1,1)(2,1,2)12 was the best fitting model. The predicted value and the actual value were in good agreement and the accuracy was high. The accuracy metrics were:ME(-0.02), RMSE (0.19), MAE (0.13), MPE (-0.32%), MAPE (1.70), and MASE (0.69). Comparing the predicted value and the actual number of cases in May-September 2018, the absolute average error and relative error were -203 cases and -8.62%, respectively. The predicted value for October-December 2018 were 2 401,2 130 and 3 643,respectively. Conclusions The ARIMA model could provide a more accurate short-term prediction of the incidence of waterborne infectious diseases in Fujian Province, and could provide a base is for risk assessment and formulation of prevention and control measures.
 

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中文著录格式: 祝寒松,,欧剑鸣,,谢忠杭,,吴生根,,林嘉威,,黄文龙.福建省介水传染病发病短期定量预测研究.环境卫生学杂志.2019;9(6):568-571,576.
英文著录格式: ZHU,Hansong,,OU,Jianming,,XIE,Zhonghang,,WU,Shenggen,,LIN,Jiawei,,HUANG,Wenlong.Quantitative Prediction on Short-term Incidence of Waterborne Diseases in Fujian..2019;9(6):568-571,576.

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