title: [Comparison on the different thresholds on the 'moving percentile method' for outbreak detection].
abstract: OBJECTIVE
  To compare the different thresholds of 'moving percentile method' for outbreak detection in the China Infectious Diseases Automated-alert and Response System (CIDARS).
  
  
  METHODS
  The thresholds of P(50), P(60), P(70), P(80) and P(90) were respectively adopted as the candidates of early warning thresholds on the moving percentile method. Aberration was detected through the reported cases of 19 notifiable infectious diseases nationwide from July 1, 2008 to June 30, 2010. Number of outbreaks and time to detection were recorded and the amount of signals acted as the indicators for determining the optimal threshold of moving percentile method in CIDARS.
  
  
  RESULTS
  The optimal threshold for bacillary and amebic dysentery was P(50). For non-cholera infectious diarrhea, dysentery, typhoid and paratyphoid, and epidemic mumps, it was P(60). As for hepatitis A, influenza and rubella, the threshold was P(70), but for epidemic encephalitis B it was P(80). For the following diseases as scarlet fever, typhoid and paratyphoid, hepatitis E, acute hemorrhagic conjunctivitis, malaria, epidemic hemorrhagic fever, meningococcal meningitis, leptospirosis, dengue fever, epidemic endemic typhus, hepatitis C and measles, it was P(90). When adopting the adjusted optimal threshold for 19 infectious diseases respectively, 64 840 (12.20%) signals had a decrease, comparing to the adoption of the former defaulted threshold (P(50)) during the 2 years. However, it did not reduce the number of outbreaks being detected as well as the time to detection, in the two year period.
  
  
  CONCLUSIONS
  The optimal thresholds of moving percentile method for different kinds of diseases were different. Adoption of the right optimal threshold for a specific disease could further optimize the performance of outbreak detection for CIDARS.
authors.affiliation: Shanghai Pudong New Area Center for Disease Control and Prevention, Shanghai 200136, China.
authors.forename: Qiao
authors.initials: Q
authors.lastname: Sun
authors.forename: Sheng-Jie
authors.initials: SJ
authors.lastname: Lai
authors.forename: Zhong-Jie
authors.initials: ZJ
authors.lastname: Li
authors.forename: Ya-Jia
authors.initials: YJ
authors.lastname: Lan
authors.forename: Hong-Long
authors.initials: HL
authors.lastname: Zhang
authors.forename: Dan
authors.initials: D
authors.lastname: Zhao
authors.forename: Lian-Mei
authors.initials: LM
authors.lastname: Jin
authors.forename: Wei-Zhong
authors.initials: WZ
authors.lastname: Yang
mesh_terms: D002681:China; D004056:Differential Threshold; D018563:Disease Notification / Q000379:methods*; D004196:Disease Outbreaks / Q000517:prevention & control*; D006801:Humans; D011159:Population Surveillance / Q000379:methods*