title: Modeling transmission of methicillin-resistant Staphylococcus aureus among patients admitted to a hospital.
abstract: OBJECTIVE
  To determine the impact of the screening test, nursing workload, handwashing rates, and dependence of handwashing on risk level of patient visit on methicillin-resistant Staphylococcus aureus (MRSA) transmission among hospitalized patients.
  
  
  METHODS
  General medical ward.
  
  
  METHODS
  Monte Carlo simulation was used to model MRSA transmission (median rate per 1,000 patient-days). Visits by healthcare workers (HCWs) to patients were simulated, and MRSA was assumed to be transmitted among patients via HCWs.
  
  
  RESULTS
  The transmission rate was reduced from 0.89 to 0.56 by the combination of increasing the sensitivity of the screening test from 80% to 99% and being able to report results in 1 day instead of 4 days. Reducing the patient-to-nurse ratio from 4.3 in the day and 6.8 at night to 3.8 and 5.7, respectively, reduced the number of nosocomial infections from 0.89 to 0.85; reducing the ratio to 1 and 1, respectively, further reduced the number of nosocomial infections to 0.32. Increases in handwashing rates by 0%, 10%, and 20% for high-risk visits yielded reductions in nosocomial infections similar to those yielded by increases in handwashing rates for all visits (0.89, 0.36, and 0.24, respectively). Screening all patients for MRSA at admission reduced the transmission rate to 0.81 per 1,000 patient-days from 1.37 if no patients were screened.
  
  
  CONCLUSIONS
  Within the ranges of parameters studied, the most effective strategies for reducing the rate of MRSA transmission were increasing the handwashing rates for visits involving contact with skin or bodily fluid and screening patients for MRSA at admission.
authors.affiliation: Department of Public Health Sciences, University of Toronto, and University Health Network, Toronto, Ontario, Canada. raboud@mshri.on.ca
authors.forename: Janet
authors.initials: J
authors.lastname: Raboud
authors.forename: Refik
authors.initials: R
authors.lastname: Saskin
authors.forename: Andrew
authors.initials: A
authors.lastname: Simor
authors.forename: Mark
authors.initials: M
authors.lastname: Loeb
authors.forename: Karen
authors.initials: K
authors.lastname: Green
authors.forename: Don E
authors.initials: DE
authors.lastname: Low
authors.forename: Allison
authors.initials: A
authors.lastname: McGeer
mesh_terms: D003362:Cost-Benefit Analysis; D003428:Cross Infection / Q000175:diagnosis / Q000453:epidemiology* / Q000382:microbiology; D018562:Disease Transmission, Infectious / Q000706:statistics & numerical data*; D006235:Hand Disinfection; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D017053:Infection Control / Q000191:economics / Q000706:statistics & numerical data*; D008403:Mass Screening / Q000191:economics / Q000706:statistics & numerical data; D016106:Methicillin Resistance; D015233:Models, Statistical; D009010:Monte Carlo Method; D009741:Nursing Staff, Hospital / Q000706:statistics & numerical data; D009864:Ontario / Q000453:epidemiology; D015995:Prevalence; D012307:Risk Factors; D012680:Sensitivity and Specificity; D013203:Staphylococcal Infections / Q000175:diagnosis / Q000453:epidemiology* / Q000382:microbiology / Q000635:transmission*; D013211:Staphylococcus aureus / Q000187:drug effects*; D016526:Workload / Q000706:statistics & numerical data