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作 者:刘天[1] 黄继贵[1] 侯清波[1] 姚梦雷[1] 阮德欣 童叶青[2] 吴杨[2] Liu Tian;Huang Ji-gui;Hou Qing-bo;Yao Meng-lei;Ruan De-xin;Tong Ye-qing;Wu Yang(Department for Infectious Disease Control and Prevention,Jingzhou Center for Disease Control and Prevention,Jingzhou 434000,Hubei Province,China;Hubei Provincial Center for Disease Control and Prevention,Wuhan 430079,Hubei Province,China)
机构地区:[1]荆州市疾病预防控制中心传染病防治所,湖北荆州434000 [2]湖北省疾病预防控制中心,武汉430079
出 处:《预防医学情报杂志》2024年第3期239-244,共6页Journal of Preventive Medicine Information
摘 要:目的比较不同时间序列模型对不同法定传染病的拟合及预测效果,为预测预警模型的选择提供参考。方法以荆州市2012—2018年肺结核、丙型病毒性肝炎(丙肝)、肾综合征出血热(HFRS)、手足口病(HFMD)、其他感染性腹泻病周发病率数据为例,分别建立SARIMA、ETS、TBATS、NNETAR、SPLINE、THETA、prophet和BSTS8种时间序列模型。预测2019年1~52周5种法定传染病报告发病率并与实际值比较。采用平均绝对误差百分比(Mean Absolute Percentage Error,MAPE)评价模型拟合及预测效果。结果其它感染性腹泻病(9.12%)、手足口病(13.80%)拟合效果最优模型为SPLINE,肺结核(3.82%)和丙肝(15.53%)、肾综合征出血热(1.83%)拟合效果最优模型为NNETAR。其它感染性腹泻病(20.27%)、肾综合征出血热(34.73%)预测效果最优模型为TBATS;手足口病(65.67%)预测效果最优模型为prophet;肺结核(16.66%)、丙肝(26.19%)预测效果最优模型为SARIMA。其它感染性腹泻病(14.89%)拟合及预测综合精度最高的模型为TBATS,手足口病(32.05%)、肺结核(6.52%)、丙肝(19.92%)和肾综合征出血热(8.50%)拟合及预测综合精度最高的模型为TBATS。结论不同模型对不同疾病拟合及预测精度均不同,应根据研究需要择优选取。Objective To compare the fitting and forecasting performance of different time series models for different notifiable infectious diseases,so as to provide reference for the selection of forecasting and early warning models.Methods Weekly incidence data of tuberculosis(TB),hepatitis C(HCV),hemorrhagic fever with renal syndrome(HFRS),hand-foot-mouth disease(HFMD),and other infectious diarrhea(Diarrhea)in Jingzhou City from 2012 to 2018 were used as examples to establish 8 time series models,including SARIMA,ETS,TBATS,NNETAR,SPLINE,THETA,prophet and BSTS.The reported incidence of 5 types of notifiable infectious diseases in the 1-52 weeks of 2019 were predicted and compared with the actual values.Mean Absolute Percentage Error(MAPE)were used to evaluate the fitting and prediction performance of different models.Results The best fitting model for Diarrhea(9.12%)and HFMD(13.80%)were SPLINE.NNETAR model showed the best fitting performance for TB(3.82%),HCV(15.53%),and HFRS(1.83%).In terms of Diarrhea(20.27%)and HFRS(34.73%),TBATS was the best predictive model.The best predictive model for HFMD(65.67%)was prophet.The SARIMA model had the best predictive performance for TB(16.66%)and HCV(26.19%).As for Diarrhea(14.89%),the model with the highest comprehensive accuracy of fitting and prediction was TBATS.The model TBATS for HFMD(32.05%),TB(6.52%),HCV(19.92%),and HFRS(8.50%)had the highest comprehensive accuracy of fitting and predicting.Conclusions Different models have different fitting and prediction accuracy for different types of infectious diseases,and the best one should be selected according to research needs.
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