[自回归积分滑动平均模型在疟疾发病率预测中的应用]
[Application of ARIMA model on prediction of malaria incidence].
作者信息
Jing Xia, Hua-Xun Zhang, Wen Lin, Su-Jian Pei, Ling-Cong Sun, Xiao-Rong Dong, Mu-Min Cao, Dong-Ni Wu, Shunxiang Cai
机构信息
Institute of Schistosomiasis Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China.
出版信息
Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi. 2016 Jan 29;28(2):135-140. doi: 10.16250/j.32.1374.2015207.
OBJECTIVE
To predict the incidence of local malaria of Hubei Province applying the Autoregressive Integrated Moving Average model (ARIMA).
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
The model of ARIMA (1, 1, 1) (1, 1, 0) 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% of predicted value of the model. The prediction effect of the model was acceptable.
CONCLUSIONS
The ARIMA model could effectively fit and predict the incidence of local malaria of Hubei Province.
目的
应用自回归积分滑动平均模型（ARIMA）预测湖北省本地疟疾的发病率。
方法
运用SPSS 13.0软件，基于2004年至2009年湖北省本地疟疾月发病率构建ARIMA模型。2010年的本地疟疾发病率数据用于模型验证和评估。
结果
ARIMA（1, 1, 1）（1, 1, 0）模型经检验为相对最佳模型，AIC为76.085，SBC为84.395。所有实际发病率数据均在模型预测值的95%范围内。该模型的预测效果可接受。
结论
ARIMA模型能够有效拟合和预测湖北省本地疟疾的发病率。
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