The comparison of two different types of baseline data regarding the performance of aberration detection algorithm for infectious disease outbreaks
10.3760/cma.j.issn.0254-6450.2011.06.011
- VernacularTitle:基于不同基线数据的传染病暴发探测方法效果比较
- Author:
Sheng-Jie LAI
1
;
Zhong-Jie LI
;
Hong-Long ZHANG
;
Ya-Jia LAN
;
Wei-Zhong YANG
Author Information
1. 中国疾病预防控制中心
- Keywords:
Infectious disease;
Outbreak;
Aberration detection algorithm
- From:
Chinese Journal of Epidemiology
2011;32(6):579-582
- CountryChina
- Language:Chinese
-
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 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.
