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Use of Stochastic Epidemic Modeling to Quantify Transmission Rates of Colonization With Methicillin-Resistant Staphylococcus Aureus in an Intensive Care Unit

Published online by Cambridge University Press:  21 June 2016

Marie Forrester  and
Anthony N. Pettitt
Marie Forrester
Affiliation:
School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
Anthony N. Pettitt*
Affiliation:
School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
*
GPO Box 2434, Brisbane, Queensland, 4001, Australia.[email protected]
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Abstract

Objective:

To consider statistical methods for estimating transmission rates for colonization of patients with methicillin-resistant Staphylococcus aureus (MRSA) in an intensive care unit (ICU) from three different sources: background contamination, non-isolated patients, and isolated patients.

Methods:

We developed statistical methods that allowed for the analysis of interval-censored, routine surveillance data and extended the general epidemic model for the flow of patients through the ICU.

Results:

Within this ICU, the rate of transmission to susceptible patients from a background source of MRSA (0.0092 case per day; 95% confidence interval [CI95], 0.0062–0.0126) is approximately double the rate of transmission from a non-isolated patient (0.0052 case per day; CI95, 0.0013–0.0096) and six times the rate of transmission from an isolated patient (0.0015 case per day; CI95, 0.0001–0.0043). We used the methodology to investigate whether transmission rates vary with workload.

Conclusion:

Our methodology has general application to infection by and transmission of pathogens in a hospital setting and is appropriate for quantifying the effect of infection control interventions. (Infect Control Hosp Epidemiol 2005;26:598-606)

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 26 , Issue 7 , July 2005 , pp. 598 - 606
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2005

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