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Use of Strain Typing Data to Estimate Bacterial Transmission Rates in Healthcare Settings

Published online by Cambridge University Press:  21 June 2016

Brian R. Jackson ,
Alun Thomas ,
Karen C. Carroll ,
Frederick R. Adler  and
Matthew H. Samore
Brian R. Jackson*
Affiliation:
Department of Medical Informatics, Salt Lake City, Utah
Alun Thomas
Affiliation:
Department of Medical Informatics and Center for High Performance Computing, Salt Lake City, Utah
Karen C. Carroll
Affiliation:
Department of Pathology, University of Utah; and ARUP Research Institute, Salt Lake City, Utah
Frederick R. Adler
Affiliation:
Departments of Mathematics and Biology, Salt Lake City, Utah
Matthew H. Samore
Affiliation:
Veteran's Administration Health Care and the Departments of Medical Informatics and Internal Medicine, University of Utah, Salt Lake City, Utah
*
ARUP Research Institute, 500 Chipeta Way, Salt Lake City, UT 84108
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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. (Infect Control Hosp Epidemiol 2005;26:638-645)

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 26 , Issue 7 , July 2005 , pp. 638 - 645
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2005

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