Transmission dynamics of methicillin-resistant Staphylococcus aureus in a medical intensive care unit

Ian Hall, Iain Barrass, Stephen Leach, Didier Pittet, Stéphane Hugonnet*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Intensive care units (ICUs) play an important role in the epidemiology of methicillin-resistant Staphyloccocus aureus (MRSA). Although successful interventions are multi-modal, the relative efficacy of single measures remains unknown. We developed a discrete time, individual-based, stochastic mathematical model calibrated on cross-transmission observed through prospective surveillance to explore the transmission dynamics of MRSA in a medical ICU. Most input parameters were derived from locally acquired data. After fitting the model to the 46 observed cross-transmission events and performing sensitivity analysis, several screening and isolation policies were evaluated by simulating the number of cross-transmissions and isolation-days. The number of all cross-transmission events increased from 54 to 72 if only patients with a past history of MRSA colonization are screened and isolated at admission, to 75 if isolation is put in place only after the results of the admission screening become available, to 82 in the absence of admission screening and with a similar reactive isolation policy, and to 95 when no isolation policy is in place. The method used (culture or polymerase chain reaction) for admission screening had no impact on the number of cross-transmissions. Systematic regular screening during ICU stay provides no added-value, but aggressive admission screening and isolation effectively reduce the number of cross-transmissions. Critically, colonized healthcare workers may play an important role in MRSA transmission and their screening should be reinforced.

Original languageEnglish
Pages (from-to)2639-2652
Number of pages14
JournalJournal of the Royal Society Interface
Volume9
Issue number75
DOIs
Publication statusPublished - 7 Oct 2012

Keywords

  • Epidemiology
  • Mathematical modelling
  • Methicillin-resistant Staphyloccocus aureus

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