Table 1 Parameter description, values and sources used in the hybrid simulation model
From: A hybrid simulation model approach to examine bacterial genome sequencing during a hospital outbreak
Parameter | Value | Source |
|---|---|---|
Initialization | ||
 Initial starting population (n) | 551 | Hospital admissions dataset |
 Number of floors and wards | Level 5 (Ward A,B,C,D); Level 2 (Ward A,B,C,D,E); SIU; GARU (Bunya, Banksia, Cassia) | Building floor plans |
Hospital Mechanics Sub Model | ||
 Population entry rate, patients per day | 24 | Calibration |
 Ward admission, transfers and stays a | see Additional file 1: Table S1-S3 | Hospital admissions dataset |
Susceptible-colonized sub model | ||
 Transmission parameter β | Level 5 = 0.153, Level 2 = 0.14, SIU = 0.086, GARU = 0.086 | Calibration |
Outbreak Management Sub Model | ||
 No WGS, outbreak number, patients with confirmed colonization | 7–15 | Expert opinion |
 No WGS, outbreak start delay, patients with confirmed colonization | 2–5 | Expert opinion |
 Microbiology test processing time, days | 2 | Expert opinion |
 Genome sequencing processing time, days (SD) b | 7 (0.5) | Expert opinion |
 Daily probability of patient being screened | Level 5 = 0.041, Level 2 = 0.043, GARU = 0.055, SIU = 0.056 | Calibration |
 Genome sequencing cost, AU$ (SD) c | 354.70 (53.2) | Clinical records |
 Microbiology test cost, AU$(SD) | 79.23 (11.88) | MBS item 69,306, PCR cost [35] |
 Bedroom cleaning cost, AU$(SD) d | 70 (10.5) | Clinical staff |
 Bed closure, AU$ (Q1-Q3) | 216 (147–285) | Page et al., 2017 [21] |
 Hourly wage for infection control nurse, AU$ (SD) | 40.33 (6.05) | Clinical staff & Queensland Health wage rates [36] |
 Executive infection control meeting e, AU$ | 462.03 (69.3) | Clinical staff & Queensland Health wage rates [36] |
Increased virulence scenario | ||
 Infection chance | 0.165 | Tischendorf et al., 2016 |
 Time till infection | 27 days [11] | Tischendorf et al., 2016 |
 Mortality (in-hospital) | 0.40 (0.5) | Chang et al., 2015 |
 Infection treatment costs, AU$ | $2650 | Chang et al., 2015 |
 End-of-life costs, AU$ | $19,696 | Reeve et al., 2018 |
Environmental contamination scenario | ||
 ET odds-ratio for patients in contaminated beds | 2.65 | Mitchell et al., 2015 |
 Bed contamination length, days | 5–10 days | Kramer et al., 2006 |