TA-23-C070 – Effect of Surgical Light Placement and Orientation in Operating Rooms on Aerosol Exposure to Healthcare Workers and Patients PDF

Laminar airflow (LAF) is used in operating rooms (OR) to prevent surgical site infections by directing clean air over the patient to wash away airborne contaminants. However, LAF is disrupted by the presence of overhead surgical lights, which create a downstream recirculation zone and also release heat, warming the surrounding fluid and causing it to rise due to buoyancy. These flow disruptions change the trajectories of aerosol particles originating within the LAF region and create the possibility of particles lingering in the surgical zone and potentially exposing patients, or, secondarily, healthcare workers (HCWs) within the LAF. This study uses computational fluid dynamics (CFD) to predict airflow for specified surgical light placements and orientations. Performing CFD simulations is computationally expensive, and the configuration space of possible surgical light placements and orientations is large and diverse. To address this challenge, we use machine learning-based adaptive sampling algorithms to build a computationally tractable surrogate model of the relationship between surgical light configuration and OR aerosol concentration. The algorithm enables us to efficiently explore the configuration space and identify the configurations that result in the greatest exposure—while laying the foundation for a broader body of work that explores the links between OR airflow and infection risk.