From: Using decision fusion methods to improve outbreak detection in disease surveillance
Sensitivity per outbreak | Sensitivity per day | Specificity | PPV | NPV | Cases required | Proportion of delay | Time to detection | AUC | AMOC | AUWROC | |
---|---|---|---|---|---|---|---|---|---|---|---|
Positive SND: scenario with a SND = 65.4 | |||||||||||
CUSUM | 1 | 0.74 | 0.83 | 0.29 | 0.97 | 0.17 | 0.25 | 4 | 0.89 | 0.90 | 0.81 |
C1 | 1 | 0.25 | 0.99 | 0.69 | 0.93 | 0.08 | 0.15 | 2 | 0.59 | 0.92 | 0.57 |
C2 | 1 | 0.38 | 0.99 | 0.77 | 0.94 | 0.08 | 0.14 | 2 | 0.66 | 0.92 | 0.64 |
C3 | 1 | 0.54 | 0.96 | 0.61 | 0.95 | 0.09 | 0.19 | 2 | 0.77 | 0.90 | 0.72 |
Farrington | 1 | 0.42 | 1.00 | 0.99 | 0.95 | 0.18 | 0.21 | 2 | 0.84 | 0.93 | 0.79 |
EWMA | 1 | 0.58 | 0.97 | 0.67 | 0.96 | 0.14 | 0.22 | 2 | 0.76 | 0.90 | 0.70 |
Majority voting | 1 | 0.56 | 1.00 | 0.98 | 0.96 | 0.10 | 0.17 | 2 | 0.78 | 0.91 | 0.73 |
Weighted majority voting | 1 | 0.53 | 1.00 | 0.99 | 0.96 | 0.13 | 0.22 | 2 | 0.77 | 0.89 | 0.71 |
Logistic regression | 1 | 0.59 | 0.99 | 0.92 | 0.96 | 0.09 | 0.16 | 2 | 0.84 | 0.94 | 0.80 |
CARTa | 1 | 0.56 | 1.00 | 0.99 | 0.96 | 0.12 | 0.19 | 2 | 0.83 | 0.92 | 0.78 |
Bayesian Networks | 1 | 0.56 | 1.00 | 1.00 | 0.96 | 0.12 | 0.19 | 2 | 0.90 | 0.93 | 0.84 |
Quasi-null SND: scenario with a SND = −1.4 | |||||||||||
CUSUM | 1 | 0.61 | 1.00 | 0.93 | 0.96 | 0.49 | 0.38 | 5 | 0.86 | 0.88 | 0.77 |
C1 | 1 | 0.17 | 0.99 | 0.64 | 0.92 | 0.24 | 0.27 | 4 | 0.55 | 0.89 | 0.53 |
C2 | 1 | 0.28 | 0.99 | 0.75 | 0.93 | 0.24 | 0.26 | 4 | 0.61 | 0.89 | 0.58 |
C3 | 1 | 0.39 | 0.97 | 0.56 | 0.94 | 0.36 | 0.31 | 5 | 0.72 | 0.86 | 0.66 |
Farrington | 1 | 0.27 | 1.00 | 1.00 | 0.93 | 0.35 | 0.34 | 4 | 0.80 | 0.91 | 0.74 |
EWMA | 1 | 0.51 | 0.94 | 0.46 | 0.95 | 0.20 | 0.24 | 4 | 0.76 | 0.90 | 0.70 |
Majority voting | 1 | 0.42 | 1.00 | 0.99 | 0.94 | 0.25 | 0.28 | 4 | 0.71 | 0.86 | 0.65 |
Weighted majority voting | 1 | 0.38 | 1.00 | 1.00 | 0.94 | 0.34 | 0.33 | 4 | 0.50 | 0.50 | 0.50 |
Logistic regression | 1 | 0.70 | 0.99 | 0.93 | 0.97 | 0.22 | 0.27 | 4 | 0.86 | 0.88 | 0.77 |
CARTa | 1 | 0.68 | 1.00 | 0.93 | 0.97 | 0.25 | 0.27 | 4 | 0.84 | 0.86 | 0.75 |
Bayesian Networks | 1 | 0.70 | 0.99 | 0.94 | 0.97 | 0.23 | 0.27 | 4 | 0.86 | 0.88 | 0.77 |
Negative SND: scenario with a SND = −89.2 | |||||||||||
CUSUM | 0.29 | 0.03 | 1.00 | 0.96 | 0.91 | 0.87 | 0.77 | 11 | 0.65 | 0.82 | 0.59 |
C1 | 0.51 | 0.05 | 0.99 | 0.25 | 0.91 | 0.73 | 0.64 | 5 | 0.52 | 0.86 | 0.49 |
C2 | 0.60 | 0.07 | 0.98 | 0.30 | 0.91 | 0.70 | 0.60 | 5 | 0.55 | 0.86 | 0.51 |
C3 | 0.78 | 0.16 | 0.96 | 0.27 | 0.92 | 0.62 | 0.50 | 6 | 0.59 | 0.82 | 0.54 |
Farrington | 0.67 | 0.09 | 0.99 | 0.46 | 0.92 | 0.64 | 0.55 | 5 | 0.60 | 0.87 | 0.56 |
EWMA | 0.98 | 0.18 | 0.95 | 0.25 | 0.92 | 0.47 | 0.37 | 5 | 0.59 | 0.87 | 0.54 |
Majority voting | 0.60 | 0.07 | 0.99 | 0.45 | 0.92 | 0.71 | 0.61 | 5 | 0.53 | 0.69 | 0.51 |
Weighted majority voting | 0.53 | 0.06 | 1.00 | 0.69 | 0.91 | 0.75 | 0.65 | 5 | 0.55 | 0.72 | 0.52 |
Logistic regression | 0.29 | 0.03 | 1.00 | 0.96 | 0.91 | 0.87 | 0.77 | 11 | 0.60 | 0.81 | 0.55 |
CARTa | 0.29 | 0.03 | 1.00 | 0.96 | 0.91 | 0.87 | 0.77 | 11 | 0.59 | 0.77 | 0.54 |
Bayesian Networks | 0.51 | 0.06 | 1.00 | 0.96 | 0.91 | 0.80 | 0.68 | 7 | 0.60 | 0.81 | 0.55 |