安庆玉, 吴隽, 姚伟. 传染病自动预警信息系统与时空聚类分析在大连市金州区风疹暴发预警中的效果比较[J]. 疾病监测, 2010, 25(7): 577-579. DOI: 10.3784/j.issn.1003-9961.2010.07.022
引用本文: 安庆玉, 吴隽, 姚伟. 传染病自动预警信息系统与时空聚类分析在大连市金州区风疹暴发预警中的效果比较[J]. 疾病监测, 2010, 25(7): 577-579. DOI: 10.3784/j.issn.1003-9961.2010.07.022
AN Qing-yu, WU Jun, YAO Wei. Comparison of the effects of the automatic early-warning information system of infectious diseases and spatial-temporal clustering analysis in predicting rubella outbreaks in Jinzhou district, Dalian city[J]. Disease Surveillance, 2010, 25(7): 577-579. DOI: 10.3784/j.issn.1003-9961.2010.07.022
Citation: AN Qing-yu, WU Jun, YAO Wei. Comparison of the effects of the automatic early-warning information system of infectious diseases and spatial-temporal clustering analysis in predicting rubella outbreaks in Jinzhou district, Dalian city[J]. Disease Surveillance, 2010, 25(7): 577-579. DOI: 10.3784/j.issn.1003-9961.2010.07.022

传染病自动预警信息系统与时空聚类分析在大连市金州区风疹暴发预警中的效果比较

Comparison of the effects of the automatic early-warning information system of infectious diseases and spatial-temporal clustering analysis in predicting rubella outbreaks in Jinzhou district, Dalian city

  • 摘要: 目的 评价并比较传染病自动预警信息系统和时空聚类分析在大连市金州区传染病暴发预警中的效果。 方法 选择某区2009年风疹预警信息作为研究对象,比较传染病自动预警信息系统和时空聚类分析结果。评价指标为灵敏度、特异度、假阳性率和假阴性率。 结果 传染病自动预警信息系统的灵敏度、特异度、假阴性率和假阳性率分别为100%、20.37%、0、79.63%;时空聚类分析的上述指标分别为95.65%、56.25%、4.35%和43.75%。 结论 传染病自动预警信息系统的预警阳性率仅为21.10%,且特异度、假阳性率、涉及病例数等方面与时空聚类分析结果相比存在一定的不足。

     

    Abstract: Objective To evaluate and compare the effects of the automatic early-warning information system of infectious diseases and spatial-temporal clustering analysis in predicting outbreaks Jinzhou district, Dalian city. Methods The early-warning information of rubella in 2009 was studied to compare the results of the early-warning system and spatial-temporal clustering analysis in terms of the sensitivity, specificity, false positive and false negative rates. Results The sensitivity, specificity, false positive and false negative rates of the automatic early-warning information system of infectious diseases was 100%,20.37%,0 and 79.63%, respectively; while the above indexes of spatial-temporal clustering analysis were 95.65%,56.25%,4.35% and 43.75%, respectively. Conclusion The automatic early-warning information system of infectious diseases has a positive rate of only 21.10%, and its specificity, false positive rate and cases coverage are relatively inferior to the corresponding performance of spatial-temporal clustering analysis.

     

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