Modelling the effect of interventions to prevent MRSA transmission within hospitals in Edmonton, Canada

Hospitalized patients are particularly susceptible to infections brought on by methicillin-resistant Staphylococcus aureus (MRSA), and these infections usually have a high morbidity and mortality rate. Several strategies can help prevent MRSA from spreading, but the efficacy of each strategy remains unclear, as most past research evaluated multiple interventions together rather than examining each one individually. To assess the effects of hand hygiene and screening, we created a novel compartmental MRSA spread framework for healthcare facilities in Edmonton, Alberta. The model accounts for MRSA patients (hospital-acquired (HA) MRSA or community-acquired (CA) MRSA colonization or infections) and isolated patients. To examine the effects of interventions, we first estimated the posterior mean of the parameters in our model, as well as a sub-model of it, using a Bayesian framework with Markov chain Monte Carlo (MCMC) techniques, utilizing data from hospitals in Edmonton. Next, we incorporated different intervention rates into the model to ascertain their effect on colonized and infected patients. One intervention is practicing hand hygiene among healthcare workers in hospitals to reduce transmission rates between susceptible individuals and MRSA patients. The other intervention is to screen patients for MRSA colonization to place them in isolation rooms swiftly. The two interventions were first examined alone, and then simultaneously. We compared the overall number of HA-MRSA colonization and infections as the intervention rates varied, and the findings show that combined interventions are more effective than individual interventions at limiting MRSA transmission in hospitals.