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预防医学  2022, Vol. 34 Issue (3): 217-221    DOI: 10.19485/j.cnki.issn2096-5087.2022.03.001
  论著 本期目录 | 过刊浏览 | 高级检索 |
基于百度指数和手足口病的疱疹性咽峡炎预测模型研究
吴昊澄, 鲁琴宝, 丁哲渊, 王心怡, 傅天颖, 杨珂, 吴晨, 林君芬
浙江省疾病预防控制中心公共卫生监测与业务指导所,浙江 杭州 310051
The Prediction model of herpangina epidemic trend based on Baidu index and hand, foot and mouth disease
WU Haocheng, LU Qinbao, DING Zheyuan, WANG Xinyi, FU Tianying, YANG Ke, WU Chen, LIN Junfen
Department of Public Health Surveillance and Advisory, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang 310051, China
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摘要 目的 利用手足口病百度指数和发病资料建立预测模型预测疱疹性咽峡炎的流行趋势,为分析监测资料有限或缺失的传染病疫情提供参考。方法 通过中国疾病预防控制信息系统收集浙江省2015年第1周至2021年第39周的手足口病发病资料,通过百度搜索收集同期手足口病和疱疹性咽峡炎的百度指数。采用小波分析法分析手足口病百度指数与其发病时间序列的关联特征;建立手足口病百度指数与其发病数的随机森林训练模型,采用平均百分比误差评价拟合效果,代入疱疹性咽峡炎百度指数预测同期流行趋势。结果 疱疹性咽峡炎百度指数和手足口病百度指数,手足口病百度指数和其发病数均显示出以26周和52周为周期的双峰型季节特征。手足口病百度指数和其发病时间序列相位差小于0.1周,建立的同期训练模型平均百分比误差为13.07%,手足口病预测发病数与实际报告发病数的一致性较好。预测疱疹性咽峡炎2015—2020年拟合发病数分别为28 822例、27 341例、28 422例、51 782例、52 457例和5 691例,2021年截至第39周发病数为48 702例。发病高峰与手足口病相似,主要在5—7月。结论 基于百度指数和手足口病发病资料建立的模型可用于预测疱疹性咽峡炎的流行趋势。
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吴昊澄
鲁琴宝
丁哲渊
王心怡
傅天颖
杨珂
吴晨
林君芬
关键词 疱疹性咽峡炎百度指数手足口病预测    
AbstractObjective To establish a prediction model of herpangina epidemic trend based on Baidu index and hand, foot and mouth disease, so as to provide insights into analyses of communicable disease epidemics with limited or missing surveillance data. Methods The incidence of hand, foot and mouth disease in Zhejiang Province during the period from the first week of 2015 through the 39th week of 2021 was retrieved from the China Information System for Disease Control and Prevention, and the Baidu index of hand, foot and mouth disease and herpangina was collected via the Baidu search engine during the same period. The correlation between the Baidu index and time series of hand, foot and mouth disease was examined using wavelet analysis. In addition, a random forest training model was created based on the Baidu index and incidence of hand, foot and mouth disease, and the fitting effectiveness was evaluated using the mean percentage error, while the Baidu index of herpangina was included in the model to predict the epidemic trend of herpangina during the study period. Results The Baidu index of herpangina and hand, foot and mouth disease, and the Baidu index and incidence of hand, foot and mouth disease all appeared two peaks at the 26th and 52th week. The phase difference was less than 0.1 week between the Baidu index and time series of hand, foot and mouth disease, and the mean percentage error of the training model was 13.07%, with high concordance between the predicted number and actual report number of cases with hand, foot and mouth disease. The numbers of herpangina cases were predicted to be 28 822, 27 341, 28 422, 51 782, 52 457 and 5 691 from 2015 to 2020, and there were totally 48 702 herpangina cases reported until the 39th week of 2021. Like hand, foot and mouth disease, the incidence of herpangina peaked between May and July. Conclusion The random forest training model based on the Baidu index and incidence of hand, foot and mouth disease is feasible to predict the epidemic trend of herpangina.
Key wordsherpangina    Baidu index    hand,foot and mouth disease    prediction
收稿日期: 2021-10-18      修回日期: 2021-12-28      出版日期: 2022-03-10
中图分类号:  R725.1  
基金资助:浙江省重点研发计划项目(2021C03038)
通信作者: 林君芬,E-mail:jflin@cdc.zj.cn   
作者简介: 吴昊澄,硕士,副主任医师,主要从事传染病监测预警工作
引用本文:   
吴昊澄, 鲁琴宝, 丁哲渊, 王心怡, 傅天颖, 杨珂, 吴晨, 林君芬. 基于百度指数和手足口病的疱疹性咽峡炎预测模型研究[J]. 预防医学, 2022, 34(3): 217-221.
WU Haocheng, LU Qinbao, DING Zheyuan, WANG Xinyi, FU Tianying, YANG Ke, WU Chen, LIN Junfen. The Prediction model of herpangina epidemic trend based on Baidu index and hand, foot and mouth disease. Preventive Medicine, 2022, 34(3): 217-221.
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http://www.zjyfyxzz.com/CN/10.19485/j.cnki.issn2096-5087.2022.03.001      或      http://www.zjyfyxzz.com/CN/Y2022/V34/I3/217
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