Skip to main content
. 2014 Jul 10;14:381. doi: 10.1186/1471-2334-14-381

Table 2.

Performance of different detection algorithms with sensitivity of 100% to detect influenza (UrgIndex-hospitalisation and ICD10-consultations), excluding data from 2009-S19 to 2010-S18

Time series
 Detection algorithms
 Outbreaks periods
 Non-epidemic periods
    Mean timeliness (days) Number of days with false alarms N = 793 Specificity (%)
UrgIndex - hospitalisations
 C2, k = 0.08, 1d
 3.7
 149
 81.2
C2, k = 0.08, 3d
 8.7
 75
 90.5
C2, k = 0.1, 1d
 3.7
 120
 84.9
C2, k = 0.1, 3d
 14.3
 56
 92.9
C3, k = 0.08, 1d
 −10.7
 560
 29.4
C3, k = 0.08, 3d
 −8.7
 497
 37.3
C3, k = 0.08, 5d
 −6.7
 446
 43.8
C3, k = 0.1, 1d
 −8.3
 511
 35.6
C3, k = 0.1, 3d
 −6.3
 440
 44.5
C3, k = 0.1, 5d
 −0.3
 384
 51.6
C3, k = 0.5, 1d
 4.0
 139
 82.5
C3, k = 0.5, 3d
 6.0
 78
 90.2
C3, k = 1, 1d
 4.0
 41
 94.8
ICD10 – consultations
 C1, k = 0.07, 1d
 1.0
 37
 95.3
C1, k = 0.07, 3d
 5.0
 23
 97.1
C1, k = 0.07, 5d
 12.3
 15
 98.1
C1, k = 0.1, 1d
 1.0
 36
 95.5
C1, k = 0.1, 3d
 5.0
 22
 97.2
C1, k = 0.1, 5d
 12.3
 14
 98.2
C2, k = 0.07, 1d
 −1.7
 34
 95.7
C2, k = 0.07, 3d
 24.7
 26
 96.7
C2, k = 0.07, 5d
 26.7
 18
 97.7
C2, k = 0.1, 1d
 6.7
 30
 96.2
C2, k = 0.1, 3d
 25.0
 22
 97.2
C2, k = 0.1, 5d
 27.0
 14
 98.2
C3, k = 0.07, 1d
 −8.0
 48
 93.9
C3, k = 0.07, 3d
 3.0
 40
 95.0
C3, k = 0.07, 5d
 5.0
 35
 95.6
C3, k = 0.1, 1d
 −8.0
 46
 94.2
C3, k = 0.1, 3d
 3.0
 36
 95.5
C3, k = 0.1, 5d
 5.0
 31
 96.1
  C3, k = 0.5, 1d 8.3 26 96.7

C1, C2, and C3 refer to the three different moving average calculations of CUSUM statistics (C1-mild, C2-medium, C3-ultra).

k is the detectable difference to the mean used to the calculation of CUSUM statistics.

Negative mean timeliness: first day signal before the outbreaks beginning, on average.

Positive mean timeliness: first day signal after the outbreaks beginning, on average.