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Modeling the Spread of Resistant Nosocomial Pathogens in an Intensive-Care Unit

Published online by Cambridge University Press:  02 January 2015

Véronique Sébille ,
Sylvie Chevret  and
Alain-Jacques Valleron
Véronique Sébille*
Affiliation:
Unité de Recherche “Epidémiologie et Sciences de l'Information” (INSERM U444), Institut Fédératif Saint-Antoine de Recherche sur la Santé (ISARS), Paris, France
Sylvie Chevret
Affiliation:
Unité de Recherche “Epidémiologie et Sciences de l'Information” (INSERM U444), Institut Fédératif Saint-Antoine de Recherche sur la Santé (ISARS), Paris, France Département de Biostatistique et Informatique Médicale, Hôpital Saint-Louis, Paris, France
Alain-Jacques Valleron
Affiliation:
Unité de Recherche “Epidémiologie et Sciences de l'Information” (INSERM U444), Institut Fédératif Saint-Antoine de Recherche sur la Santé (ISARS), Paris, France
*
Unité de Recherche Epidémiologie et Sciences de l'Information (INSERM U444), Institut Fédératif Saint-Antoine de Recherche sur la Santé (ISARS), 27, rue Chaligny, 75571 Paris Cedex 12, France
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Abstract

Objectives:

To show the value of mathematical modeling in simulating the spread of nosocomial pathogens in an intensive-care unit (ICU), to provide a framework for listing available knowledge; to predict the benefits of various control measures; and to supplement the epidemiological assessment of these measures.

Design:

Simulated outbreak of a nosocomial pathogen in an ICU, based on a deterministic compartmental model describing both person-to-person spread and indirect spread between patients through staff members.

Interventions:

Simulation of three typical colonization control measures: effective handwashing compliance among staff members, ICU antimicrobial policy, and curtailing ICU admission of colonized patients.

Results:

In controlling colonization, effective handwashing compliance reduced staff member colonization, but only moderately limited patient colonization unless the ICU was isolated strictly by curtailing the admission of colonized patients. The impact of antibiotic policy was very slight.

Conclusions:

In the field of nosocomial infection, mathematical modeling appears to be a valuable tool that can be used to evaluate the magnitude of the expected effects of control strategies and to guide the selection of the best randomized clinical trials to pursue.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 18 , Issue 2 , February 1997 , pp. 84 - 92
Copyright
Copyright © The Society for Healthcare Epidemiology of America 1997

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