| 王小莉,王全意,刘东磊,曾大军,程贺,李素,段玮,黎新宇,栾荣生,贺雄.采用北京市麻疹的暴发模拟数据比较几种预警模型的功效[J].Chinese journal of Epidemiology,2009,30(2):159-162 |
| 采用北京市麻疹的暴发模拟数据比较几种预警模型的功效 |
| Comparison between early outbreak detection models and simulated Outbreaks of measles in Beijing |
| Received:July 31, 2008 |
| DOI： |
| KeyWord: 麻疹 预警 指数加权移动平均 时空重排扫描 |
| English Key Word: Measles Early outbreak detection Exponential weighted moving average Space-time permutation scan-statistic |
| FundProject:北京市自然科学基金资助项目(7082047)；北京市优秀人才培养资助项目(2007id0302600112) |
| Author Name | Affiliation | E-mail | | WANG Xiao-li | Beijing Center for Disease Control and Prevention, Beijing 100013, China | | | WANG Quan-yi | Beijing Center for Disease Control and Prevention, Beijing 100013, China | | | LIU Dong-lei | Beijing Center for Disease Control and Prevention, Beijing 100013, China | | | ZENG Da-jun | 中国科学院自动化研究所 | | | CHENG He | 中国科学院自动化研究所 | | | LI Su | 中国科学院自动化研究所 | | | DUAN Wei | Beijing Center for Disease Control and Prevention, Beijing 100013, China | | | LI Xin-yu | Beijing Center for Disease Control and Prevention, Beijing 100013, China | | | LUANG Rong-sheng | 四川大学华西医学中心公共卫生学院 | | | HE Xiong | Beijing Center for Disease Control and Prevention, Beijing 100013, China | Email:hexiong@vip.163.com |
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| Abstract: |
| 优选出北京市麻疹的最佳预警模型及其参数，为其自动预警提供技术支持。方法利用暴发模拟软件生成一系列不同性质的暴发信号，将其添加到北京市2005-2007年麻疹的实际日报数中。 |
| English Abstract: |
| Using simulated outbreaks to choose the optimal model and its related parameters on measles so as to provide technical support for developing an Auto Warning System(AWS).Methods AEGiS-Cluster Creation Tool was applied to simulate a range oftmique outbreak signals.Then these simulations were added to the aetnal daily counts of measles from the National Disease Surveillance System,between 2005 and 2007.Exponential weighted moving average(EWMA),C1-MILD(C1),C2.MEDIUM(C2).C3-ULTRA(C3)and space.time permutation scar statistic model were comprehensively applied to detect these simulations.Tools for evaluation as Youden's index and detection time were calculated to optimize parameters before an optimal model was finally chosen.Results EWMA(λ=0.6,κ=1.0),C1(κ=0.1,H=3σ),C2(k=0.1,H=30),C3(κ=1.0,H=4σ)and space-time permutation scan statistic(maximum temporal cluster size=7 d,maximum spatial cluster size=5 km)appeared to be the optimal parameters among these models.Youden's index of EWMA was 90.8%and detection time being 0.121 d.Youden's index of C1 was 88.7%and detection time being 0.142 d.Youden's index of C2 was 92.9%and detection time being 0.121 d.Youden's index of C3 was 87.9%and detection time being 0.058 d.Youden's index of space-time permutation scan statistic was 94.3%and detection time being 0.176 d.Conelusion Among these five early warning detection models.space-time permutation scan statistic model had the highest efficacy. |
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