A stochastic mathematical model of methicillin resistant Staphylococcus aureus transmission in an intensive care unit: predicting the impact of interventions
Related Experiment Video
Updated: Jul 18, 2026
Development and Assessment of Intracellular Infection Models for Staphylococcus aureus
Published on: January 17, 2025
E S McBryde1, A N Pettitt, D L S McElwain
1School of Mathematical Sciences, Gardens Point Campus, Queensland University of Technology, 2 George St, Brisbane, Australia. e.mcbryde@qut.edu.au
Objectives:
To estimate the transmission rate of MRSA in an intensive care unit (ICU) in an 800 bed Australian teaching hospital and predict the impact of infection control interventions.
Methods:
A mathematical model was developed which consisted of four compartments: colonised and uncolonised patients and contaminated and uncontaminated health-care workers (HCWs). Patient movements, MRSA acquisition and daily prevalence data were collected from an ICU over 939 days. Hand hygiene compliance and the probability of MRSA transmission from patient to HCW per discordant contact were measured during the study. Attack rate and reproduction ratio were estimated using Bayesian methods. The impact of a number of interventions on attack rate was estimated using both stochastic and deterministic versions of the model.
Results:
The mean number of secondary cases arising from the ICU admission of colonised patients, also called the ward reproduction ratio, R(w), was estimated to be 0.50 (95% CI 0.39-0.62). The attack rate was one MRSA transmission per 160 (95% CI 130-210) uncolonised-patient days. Results were not sensitive to uncertainty in measured model parameters (hand hygiene rate and transmission probability per contact). Hand hygiene was predicted to be the most effective intervention. Decolonisation was predicted to be relatively ineffective. Increasing HCW numbers was predicted to increase MRSA transmission, in the absence of patient cohorting. The predictions of the stochastic model differed from those of the deterministic model, with lower levels of colonisation predicted by the stochastic model.
Conclusions:
The number of secondary cases of MRSA colonisation within the ICU in this study was below unity. Transmission of MRSA was sustained through admission of colonised patients. Stochastic model simulations give more realistic predictions in hospital ward settings than deterministic models. Increasing staff does not necessarily lead to reduced transmission of nosocomial pathogens.
Insights
This study estimated Methicillin-resistant Staphylococcus aureus (MRSA) transmission in an ICU, finding hand hygiene most effective. Increasing healthcare workers (HCWs) may increase MRSA spread without patient cohorting.
Area of Science:
- Infectious Disease Epidemiology
- Mathematical Modeling
- Hospital Infection Control
Background:
- Methicillin-resistant Staphylococcus aureus (MRSA) poses a significant threat in intensive care units (ICUs).
- Understanding transmission dynamics is crucial for effective infection control.
- Previous models have limitations in predicting real-world hospital ward scenarios.
Purpose of the Study:
- To quantify MRSA transmission rates within an Australian teaching hospital ICU.
- To predict the impact of various infection control interventions on MRSA spread.
- To compare the predictive accuracy of stochastic and deterministic mathematical models.
Main Methods:
- Developed a four-compartment mathematical model (patients and healthcare workers).
- Collected patient movement, MRSA acquisition, and prevalence data over 939 days.
- Estimated attack rates and reproduction ratios using Bayesian methods and simulated intervention impacts.
Main Results:
- The ward reproduction ratio (R(w)) was estimated at 0.50, indicating transmission below unity.
- MRSA transmission occurred at a rate of 1 per 160 uncolonised-patient days.
- Hand hygiene was the most effective intervention; decolonisation was less effective; increasing HCW numbers potentially increased transmission.
Conclusions:
- MRSA transmission within the ICU was primarily sustained by the admission of colonised patients.
- Stochastic models provide more realistic predictions for hospital ward settings than deterministic models.
- Increasing healthcare worker numbers does not guarantee reduced nosocomial pathogen transmission without complementary strategies.
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