文章摘要
赖圣杰,李中杰,张洪龙,兰亚佳,杨维中.基于不同基线数据的传染病暴发探测方法效果比较[J].中华流行病学杂志,2011,32(6):579-582
基于不同基线数据的传染病暴发探测方法效果比较
The comparison of two different types of baseline data regarding the performance of aberration detection algorithm for infectious disease outbreaks
收稿日期:2010-11-11  出版日期:2014-09-10
DOI:
中文关键词: 传染病  暴发  探测
英文关键词: Infectious disease  Outbreak  Aberration detection algorithm
基金项目:国家科技重大专项(2009ZX10004-201);国家科技支撑计划(2008BAI56B02);中国-世界卫生组织合作项目(WPCHN1002405)
作者单位E-mail
赖圣杰 中国疾病预防控制中心, 北京 102206  
李中杰 中国疾病预防控制中心, 北京 102206 lizj@chinacdc.cn 
张洪龙 中国疾病预防控制中心, 北京 102206  
兰亚佳 四川大学华西公共卫生学院  
杨维中 中国疾病预防控制中心, 北京 102206 yangwz@chinacdc.cn 
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中文摘要:
      目的 比较采用不同基线数据传染病暴发探测方法的效果.方法 以2009年6个省(市)报告的手足口病(HFMD)病例和暴发为数据来源,对C1、C2、C3三种传染病暴发探测方法均选用基于"区分与不区分周末和工作日"两种基线数据进行运算,以暴发探测时间(TTD)和错误预警率(FAR)作为算法功效的评价指标,比较C1、C2和C3分别基于两种基线数据的暴发探测效果.结果 2009年6个省(市)共报告了HFMD病例405 460例,工作日期问每县每日平均报告1.78例,周末每县每日平均报告1.29例,两者差异具有统计学意义(P<0.01).采用不区分周末和工作日的基线数据时,C1、C2和C3的最优阈值分别为0.2、0.4和0.6,TTD均为1 d,FAR分别为5.33%、4.88%和4.50%;采用区分周末和工作日的基线数据时,C1、C2和C3的最优阈值分别为0.4、0.6和1.0,TTD均为1 d,FAR分别为4.81%、4.75%和4.16%,三种方法的FAR均低于采用不区分周末和工作日的基线数据.结论 HFMD在工作日与周末报告的病例数有显著差异;C1、C2和C3三种异常探测方法采用区分周末和工作日的基线数据可降低FAR,提高暴发探测的准确性.
英文摘要:
      Objective To compare the performance of aberration detection algorithm for infectious disease outbreaks, based on two different types of baseline data. Methods Cases and outbreaks of hand-foot-and-mouth disease (HFMD) reported by six provinces of China in 2009 were used as the source of data. Two types of baseline data on algorithms of C1,C2 and C3 were tested, by distinguishing the baseline data of weekdays and weekends. Time to detection (TTD) and false alarm rate (FAR) were adopted as two evaluation indices to compare the performance of 3 algorithms based on these two types of baseline data. Results A total of 405 460 cases of HFMD were reported by 6 provinces in 2009. On average,each county reported 1.78 cases per day during the weekdays and 1.29 cases per day during weekends, with significant difference (P<0.01) between them. When using the baseline data without distinguish weekdays and weekends, the optimal thresholds for C1, C2 and C3 was 0.2,0.4 and 0.6 respectively while the TTD of C1,C2 and C3 was all 1 day and the FARs were 5.33%,4.88% and 4.50% respectively. On the contrast, when using the baseline data to distinguish the weekdays and weekends, the optimal thresholds for C1, C2 and C3 became 0.4,0.6 and 1.0 while the TTD of Cl,C2 and C3 also appeared equally as 1 day.However, the FARs became 4.81%,4.75% and 4.16% respectively, which were lower than the baseline data from the first type.Conclusion The number of HFMD cases reported in weekdays and weekends were significantly different, suggesting that when using the baseline data to distinguish weekdays and weekends, the FAR of C1, C2 and C3 algorithm could effectively reduce so as to improve the accuracy of outbreak detection.
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