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[关于传染病暴发异常检测算法性能的两种不同类型基线数据的比较]

[The comparison of two different types of baseline data regarding the performance of aberration detection algorithm for infectious disease outbreaks].

作者信息

Lai Sheng-jie, Li Zhong-jie, Zhang Hong-long, Lan Ya-jia, Yang Wei-zhong

机构信息

Chinese Center for Disease Control and Prevention, Beijing, China.

出版信息

Zhonghua Liu Xing Bing Xue Za Zhi. 2011 Jun;32(6):579-82.

PMID:21781476
Abstract

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 C1, 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.

摘要

目的

基于两种不同类型的基线数据,比较传染病暴发异常检测算法的性能。

方法

以2009年中国六个省份报告的手足口病(HFMD)病例和疫情作为数据来源。通过区分工作日和周末的基线数据,对C1、C2和C3算法的两种类型基线数据进行测试。采用检测时间(TTD)和误报率(FAR)作为两个评估指标,比较基于这两种类型基线数据的3种算法的性能。

结果

2009年6个省份共报告手足口病病例405460例。平均而言,每个县在工作日每天报告1.78例,周末每天报告1.29例,两者之间存在显著差异(P<0.01)。当不区分工作日和周末使用基线数据时,C1、C2和C3的最佳阈值分别为0.2、0.4和0.6,而C1、C2和C3的TTD均为1天,FAR分别为5.33%、4.88%和4.50%。相比之下,当使用基线数据区分工作日和周末时,C1、C2和C3的最佳阈值变为0.4、0.6和1.0,而C1、C2和C3的TTD同样为1天。然而,FAR分别变为4.81%、4.75%和4.16%,低于第一种类型的基线数据。

结论

工作日和周末报告的手足口病病例数存在显著差异,表明在使用基线数据区分工作日和周末时,C1、C2和C3算法的FAR可有效降低,从而提高暴发检测的准确性。

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引用本文的文献

1
Improving the performance of outbreak detection algorithms by classifying the levels of disease incidence.通过对疾病发病率进行分类来提高疫情检测算法的性能。
PLoS One. 2013 Aug 19;8(8):e71803. doi: 10.1371/journal.pone.0071803. eCollection 2013.