Chin J Schisto Control ›› 2016, Vol. 28 ›› Issue (2): 135-140.

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Application of ARIMA model on prediction of malaria incidence

XIA Jing,ZHANG Hua-xun,LIN Wen,PEI Su-jian,SUN Ling-cong,DONG Xiao-rong,CAO Mu-min,WU Dong-ni,CAI Shun -xiang*   

  1. Institute of Schistosomiasis Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China
  • Online:2016-04-19 Published:2016-04-20
  • Contact: CAI Shun ?xiang

ARIMA模型在疟疾发病率预测中的应用

夏菁,张华勋,林文,裴速建,孙凌聪,董小蓉,曹慕民,吴冬妮,蔡顺祥*   

  1. 湖北省疾病预防控制中心血吸虫病防治研究所 (武汉430079)
  • 通讯作者: 蔡顺祥
  • 作者简介:夏菁, 女, 博士, 主管医师。研究方向: 寄生虫病流行病学

Abstract: Objective Objective To predict the incidence of local malaria of Hubei Province applying the Autoregressive Integrated Moving Average model(ARIMA) . Methods Methods SPSS 13.0 software was applied to construct the ARIMA model based on the monthly local malaria incidence in Hubei Province from 2004 to 2009. The local malaria incidence data of 2010 were used for model validation and evaluation. Results Results The model of ARIMA(1,1,1)(1,1,0) 12 was tested as relatively the best optimal with the AIC of 76.085 and SBC of 84.395. All the actual incidence data were in the range of 95% CI of predicted value of the model. The prediction effect of the model was acceptable. Conclusion Conclusion The ARIMA model could effectively fit and predict the incidence of local malaria of Hubei Province.

Key words: Malaria, Time series, ARIMA model, Prediction, Incidence

摘要: 目的 目的 应用自回归求和移动平均模型 (Autoregressive Integrated Moving Average Model, ARIMA) 进行湖北省本地 疟疾发病率预测。 方法 方法 应用SPSS 13.0软件对2004-2009年湖北省本地疟疾发病率构建ARIMA模型, 并以2010年发 病率数据检验模型, 评价模型拟合及预测效果。 结果 结果 经检验确认ARIMA (1,1,1) (1,1,0) 12模型拟合效果相对最 优, AIC=76.085, SBC=84.395, 发病率实际值均在预测值的95%可信区间内, 表明模型预测效果较好。 结论 结论 ARIMA模 型可对湖北省本地疟疾发病率进行较好的拟合和预测。

关键词: 疟疾, 时间序列, ARIMA模型, 预测, 发病率

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