Parameters Used in 1-Way Sensitivity Analyses and in Monte Carlo Simulations
| Parameter | 95% confidence interval | Distribution |
| Node 1 | 0.7–1.0 | Triangular (minimum, 0.7; likeliest, 0.79; maximum, 1) |
| Node 2 | 0.84–1.0 | Triangular (minimum, 0.84; likeliest, 0.97; maximum, 1) |
| Node 3 | 0.85–1.0 | Triangular (minimum, 0.85; likeliest, 0.95; maximum, 1) |
| Node 4 | 0.4–0.6 | Triangular (minimum, 0.4; likeliest, 0.52; maximum, 0.6) |
| Node 5 | 0.7–0.9 | Triangular (minimum, 0.7; likeliest, 0.82; maximum, 0.9) |
| Node 6 | 0.85–0.95 | Triangular (minimum, 0.85; likeliest, 0.9; maximum, 0.95) |
| Node 7 | 0.60–0.85 | Triangular (minimum, 0.75; likeliest, 0.81; maximum, 0.85) |
| Node 8 | 0.70–0.90 | Triangular (minimum, 0.70; likeliest, 0.85; maximum, 0.9) |
| Node 9 | 0.5–0.7 | Triangular (minimum, 0.5; likeliest, 0.53; maximum, 0.7) |
| Node 10 | 0.8–1.0 | Triangular (minimum, 0.8; likeliest, 0.95; maximum, 1) |
Nodes N1–N10 refer to decision tree model in Figure 1.