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Modeling the Spread of Methicillin-Resistant Staphylococcus aureus (MRSA) Outbreaks throughout the Hospitals in Orange County, California

Published online by Cambridge University Press:  02 January 2015

Bruce Y. Lee*
Affiliation:
University of Pittsburgh, Pittsburgh, Pennsylvania
Sarah M. McGlone
Affiliation:
University of Pittsburgh, Pittsburgh, Pennsylvania
Kim F. Wong
Affiliation:
University of Pittsburgh, Pittsburgh, Pennsylvania
S. Levent Yilmaz
Affiliation:
University of Pittsburgh, Pittsburgh, Pennsylvania
Taliser R. Avery
Affiliation:
Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
Yeohan Song
Affiliation:
University of Pittsburgh, Pittsburgh, Pennsylvania
Richard Christie
Affiliation:
University of Pittsburgh, Pittsburgh, Pennsylvania
Stephen Eubank
Affiliation:
Virginia Bioinformatics Institute, Blacksburg, Virginia
Shawn T. Brown
Affiliation:
University of Pittsburgh, Pittsburgh, Pennsylvania Pittsburgh Supercomputing Center, Pittsburgh, Pennsylvania
Joshua M. Epstein
Affiliation:
Johns Hopkins University, Baltimore, Maryland
Jon I. Parker
Affiliation:
Johns Hopkins University, Baltimore, Maryland
Donald S. Burke
Affiliation:
University of Pittsburgh, Pittsburgh, Pennsylvania
Richard Platt
Affiliation:
Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
Susan S. Huang
Affiliation:
School of Medicine, University of California, Irvine, California
*
University of Pittsburgh, 200 Meyran Avenue, Suite 200, Pittsburgh, PA 15213 (BYLl@pitt.edu)

Abstract

Background.

Since hospitals in a region often share patients, an outbreak of methicillin-resistant Staphylococcus aureus (MRSA) infection in one hospital could affect other hospitals.

Methods.

Using extensive data collected from Orange County (OC), California, we developed a detailed agent-based model to represent patient movement among all OC hospitals. Experiments simulated MRSA outbreaks in various wards, institutions, and regions. Sensitivity analysis varied lengths of stay, intraward transmission coefficients (β), MRSA loss rate, probability of patient transfer or readmission, and time to readmission.

Results.

Each simulated outbreak eventually affected all of the hospitals in the network, with effects depending on the outbreak size and location. Increasing MRSA prevalence at a single hospital (from 5% to 15%) resulted in a 2.9% average increase in relative prevalence at all other hospitals (ranging from no effect to 46.4%). Single-hospital intensive care unit outbreaks (modeled increase from 5% to 15%) caused a 1.4% average relative increase in all other OC hospitals (ranging from no effect to 12.7%).

Conclusion.

MRSA outbreaks may rarely be confined to a single hospital but instead may affect all of the hospitals in a region. This suggests that prevention and control strategies and policies should account for the interconnectedness of health care facilities.

Type
Original Articles
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2011

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