Abstract
<h3>Background</h3> Emergency medical service (EMS) vehicles may pose pathogen exposure risks for patients on route to a healthcare facility. One organism, particularly of concern in this environment, is methicillin-resistant Staphylococcus aureus (MRSA). The objective of this study was to develop a surface transmission model for estimating MRSA infection risk reductions associated with motion-activated ultraviolet (UV-C) light disinfection on surfaces in between hand-to-surface contacts in EMS vehicles. <h3>Methods</h3> A published mathematical transmission model was adapted to estimate MRSA transmission and infection risk for a patient during an emergency call. Two simulated scenarios were explored: 1) Baseline (no UV-C) and 2) UV-C disinfection (intervention) on a heart monitor, keyboard and portable radio in between contacts. The simulation was adapted to estimate the probability of a patient's wound exposure to MRSA and subsequent infection risk during a single transport. Variability and uncertainty in EMS personnel hand-to-medical equipment behavior and in MRSA concentration on high contact surfaces were accounted for within the model using a Monte Carlo simulation approach, where a series of potential outcomes could be considered. <h3>Results</h3> Over a 34-minute period, MRSA concentrations on both patient's wound and paramedics' hands reached a steady state. Baseline infection (no UV-C light) risk was 3.5 × 10-8 on average. The infection risk for the UV-C light disinfection scenario was 2.53 × 10-8 on average. The reduction in mean infection risk was 27.8%. With the UV-C light intervention, there was a decrease in the overall MRSA surface concentrations within the EMS vehicle. <h3>Conclusions</h3> This mathematical simulation demonstrates that UV-C light disinfection within EMS vehicle may reduce MRSA infection risks for patients with when only three surfaces are targeted for treatment. Future studies are planned to better characterize paramedic behaviors that drive surface and hand contamination rates and to evaluate variables of UV-C light efficacy.
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