Selected article for: "specificity sensitivity and standard deviation"

Author: Thilo Reich; Marcin Budka
Title: A Proof Of Concept For A Syndromic Surveillance System Based On Routine Ambulance Records In The South-west Of England, For The Influenza Season 2016/17
  • Document date: 2018_11_9
  • ID: j3o0fko1_59
    Snippet: The start of the increase in pyrexia cases defined by a final change of the CR 21 to >1, was detected on the 24/09/16 (week 38/2016) with 70 pyretic patients (11.2% of 633 calls, Figure 4 ). This value is 6.8% below the baseline (76.2) and within the standard deviation (23.48), which would not be detectable using a threshold method. This start of the seasonal increase of infections was detected earlier than influenza cases by the ECDC, which iden.....
    Document: The start of the increase in pyrexia cases defined by a final change of the CR 21 to >1, was detected on the 24/09/16 (week 38/2016) with 70 pyretic patients (11.2% of 633 calls, Figure 4 ). This value is 6.8% below the baseline (76.2) and within the standard deviation (23.48), which would not be detectable using a threshold method. This start of the seasonal increase of infections was detected earlier than influenza cases by the ECDC, which identified the start in week 46/2016 [32]. However, this might be due to the fact that the sentinel surveillance runs between October and March and thus had not started when our system detected an increase in cases [33] To establish the performance of the method, the outbreak detected by PHE was considered the ground truth [31] which allowed to estimate a specificity of 99.7% and sensitivity of 100% . Because of the limited data available the sensitivity and specificity can only be considered crude estimates and should be interpreted accordingly. These can be robustly measure in the future once more specific data is available.

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