基于ARIMA乘积季节模型预测产超广谱β-内酰胺酶大肠埃希菌流行趋势研究  

Forecasting incidence of extended spectrum β-lactamases-producing Escherichia coli by multiple seasonal ARIMA model

作　　者：储文杰[1] 金凯玲[1] 林凯[1] 单欢[1] 陈伟国[1] CHU Wen-jie;JIN Kai-ling;LIN Kai;SHAN Huan;CHEN Wei-guo(Department of Nosocomial Infection,Hangzhou,Zhejiang Hospital,Zhejiang 310013,China)

机构地区：[1]浙江医院医院感染管理科,浙江杭州310013

出　　处：《预防医学》2018年第7期680-684,共5页CHINA PREVENTIVE MEDICINE JOURNAL

基　　金：浙江医院医药卫生科学研究基金项目(2015YJ008)

摘　　要：目的利用产超广谱β-内酰胺酶(ESBLs)大肠埃希菌监测数据建立求和自回归移动平均(ARIMA)乘积季节模型,分析并预测ESBLs大肠埃希菌流行趋势。方法使用2010—2016年浙江医院产ESBLs大肠埃希菌感染的逐月检出例数拟合ARIMA乘积季节模型,以平均绝对百分误差(MAPE)及贝叶斯信息准则(BIC)评价模型的可行性。以2017—2018年2月产ESBLs大肠埃希菌感染的逐月检出例数作为评估模型的样本,验证模型的预测效果。结果筛选出的最优模型为ARIMA(0,1,1)(0,1,1)12,MAPE为14.76,BIC为2.01,模型残差序列的Ljung-Box统计量Q=16.79(P=0.40),模型拟合良好。所选模型预测的2017—2018年2月产ESBLs大肠埃希菌感染检出例数与实际值的平均相对误差为14.08%,实际值均在预测值95%CI内。结论 ARIMA乘积季节模型对产ESBLs大肠埃希菌感染检出例数的拟合情况较好,可用于产ESBLs大肠埃希菌感染的短期预测和动态分析。Objective To predict monthly incidents of extended spectrum β-Lactamases （ESBLs）-producing Escherichia coli in Zhejiang Hospital by establishing multiple seasonal autoregressive integrated moving average （ARIMA） model, so as to provide scientific evidence for reducing the incidents of nosocomial infection of ESBLs producing Escherichia coli. Methods Multiple seasonal ARIMA model was established by monthly records of ESBLs producing Escherichia coli from 2010 to 2016 in Zhejiang hospital. Monthly incidents of ESBLs producing Escherichia coli from 2017 to February 2018 were used to verify the predicted result. The predictions were evaluated by models of mean absolute percent error （MAPE） and bayesian information criterion （BIC） . Results The optional model for the monthly incidence from 2010 to 2016 was ARIMA （0, 1, 1） （0, 1, 1）12 ~ The MAPE was 14.76, BIC was 2.01, and the Ljung-Box statistics value Q was 16.79 （P=0.40） . These parameters suggested a good model fitting. The average relative error between the predictive value and the actual value of the monthly incidents ESBLs producing Escherichia coli from 2017 to February 2018 was 14.08%. The actual values were within the 95% confidence interval. Conclusion The multiple seasonal ARIMA model of ARIMA （0, 1, 1） （0, 1, 1 ）12 fits and can be used for short-term prediction and dynamic analysis of the incidents of ESBLs producing Escherichia celi in Zhejiang Hospital.

关 键 词：超广谱Β-内酰胺酶 大肠埃希菌 耐药性 ARIMA乘积季节模型 

分 类 号：R181.3[医药卫生—流行病学]