ARIMA与ARIMAX模型在钉螺密度预测中的应用  

Application of ARIMA and ARIMAX models in forecasting the density of Oncomelania hupensis

作　　者：陈曦[1] 洪希成[2] 徐兴建[2] 魏凤华[2] 朱惠国[2] 

机构地区：[1]武汉市中心医院医学资讯科,武汉430014 [2]湖北省疾病预防控制中心

出　　处：《公共卫生与预防医学》2014年第2期6-9,共4页Journal of Public Health and Preventive Medicine

基　　金：国家科技支撑计划<控制钉螺扩散新技术研究>(2009BAI78B03);湖北省卫生厅血防专项(XF-2010-6);中国气象局气候变化专项子项目<西湖地区血吸虫病传播气候环境研究>(CCSF-2014-09)

摘　　要：目的探讨ARIMA与ARIMAX模型在预测钉螺密度的适用性,为湖北省钉螺的控制提供参考依据。方法收集湖北省潜江市1980-2012年的钉螺查螺资料及气象资料,应用ARIMA与ARIMAX模型对潜江市钉螺密度进行预测分析。结果钉螺密度的ARIMA模型为(1-B)(1-0.643B6)dt=εt,ARIMAX模型为dt=16.371+(-0.522-0.363B)temt+(1+0.590B)εt。ARIMA模型与ARIMAX模型的参数差异均有统计学意义(P<0.05),实测值和预测值的趋势基本上一致,实测值均在预测值的95%可信区间内。结论 ARIMA模型与ARIMAX模型可以应用于钉螺密度的预测,具有较好的精度。Objective To discuss the application of ARIMA and ARIMAX models in forecasting the density of snails, and provide basis for controlling snails in Hubei province. Methods Retrospective survey method was used to collect oncomelania data and climate data in Qianjiang city, Hubei province, from 1980 to 2012 yearly. Auto-regressive integrated moving average （ARIMA） model and multivariate ARIMA （ARIMAX） were used to predict the snail density. Results The ARIMA and ARIMAX models of oncomelania density were （ 1 -B ） （ 1 - 0. 643B6 ） d, = ~, and d~ = 16. 371 ＋ （ - 0. 522 - 0. 363B）tern,＋（ 1 ＋0. 590B）~,, respectively. The parameters of ARIMA and ARIMAX models were statistically significant （P 〈0. 05）. The trend of measured values and predicted values were consistent, and all measured values were in the 95% confidence interval of the predicted values of the two models. Conclusions ARIMA and ARIMAX models can be used to predict the density of snails, which were of highly predictive preciseness.

关 键 词：钉螺密度 求和自回归移动平均模型 动态回归模型 预测 

分 类 号：R383.24[医药卫生—医学寄生虫学]