Abstract
OBJECTIVE: To create an affordable and accurate method for continuously monitoring bacterial transmission rates in healthcare settings. DESIGN: We present a discrete simulation model that relies on the relationship between in-hospital transmission rates and strain diversity. We also present a proof of concept application of this model to a prospective molecular epidemiology data set to estimate transmission rates for Pseudomonas aeruginosa and Staphylococcus aureus. SETTING: Inpatient units of an academic referral center. PATIENTS: All inpatients with nosocomial infections. INTERVENTION: Mathematical model to estimate transmission rates. RESULTS: Maximum likelihood estimates for transmission rates of these two species on different hospital units ranged from 0 to 0.36 transmission event per colonized patient per day. CONCLUSIONS: This approach is feasible, although estimates of transmission rates based solely on strain typed clinical cultures may be too imprecise for routine use in infection control. A modest level of surveillance sampling substantially improves the estimation accuracy.
Original language | English (US) |
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Pages (from-to) | 638-645 |
Number of pages | 8 |
Journal | Infection control and hospital epidemiology |
Volume | 26 |
Issue number | 7 |
DOIs | |
State | Published - Jul 2005 |
Externally published | Yes |
ASJC Scopus subject areas
- Epidemiology
- Microbiology (medical)
- Infectious Diseases