基于谷歌趋势的乙型肝炎预测模型  

Hepatitis B prediction model based on Google trends

作　　者：杨艳红[1] 曾庆[1] 赵寒[2] 易娟[2] 李勤[2] 夏宇 

机构地区：[1]重庆医科大学公共卫生与管理学院卫生统计教研室,重庆400016 [2]重庆市疾病预防控制中心,重庆400042

出　　处：《上海交通大学学报（医学版）》2013年第2期204-208,共5页Journal of Shanghai Jiao tong University:Medical Science

基　　金：重庆市卫生局科技计划项目(2011-2-583)~~

摘　　要：目的探讨结合谷歌趋势进行预测的状态空间模型应用于乙型肝炎的可行性。方法采用SAS 9.13软件进行数据分析和建模。以2005年1月2日—2010年12月26日的重庆市乙型肝炎实际发病数和谷歌趋势数据建立状态空间模型,并用2011年1月2日—6月19日的实际发病数据进行模型验证。结果重庆市乙型肝炎发病情况适合用结合谷歌趋势指数进行预测的状态空间模型,预测值与实际值的平均相对误差为7.44%,预测效果良好。结论结合网络搜索引擎的数据对乙型肝炎的预测是可行的。Objective To investigate the feasibility to predict hepatitis B with the state space model in combination of Google trends. Methods SAS 9.13 software was used for data analysis and modeling. The state space model was established with the data of actual incidence of hepatitis B in Chongqing and those from Google trends between January 2, 2005 and December 26, 2010, and the data of actual incidence of hepatitis B between January 2, 2011 and June 19, 2011 was used for model validation. Results The state space model in combination with Google trends was useful to predict the prevalence of hepatitis B in Chongqing. The mean relative error for predictive value and actual value was 7.44%, which indicated a favorable prediction result. Conclusion It is feasible to predict hepatitis B in combination with data from network based searching.

关 键 词：谷歌趋势 状态空间模型 预测 乙型肝炎 

分 类 号：R512.62[医药卫生—内科学]