Abstract
The COVID-19 pandemic has highlighted the significant infection risks posed by aerosol-generating procedures (AGPs), such as intubation and cardiopulmonary resuscitation (CPR). Despite existing protective measures, high-risk environments like these require more effective safety solutions. In response, our research team has focused on developing a novel respiratory barrier enclosure designed to enhance the safety of healthcare workers and patients during AGPs. We developed a hood that covers the patient's respiratory area, incorporating a negative pressure system to contain aerosols. Using computational fluid dynamics (CFD) analysis, we optimized the hood's design and adjusted the negative pressure levels based on simulations of droplet dispersion. To test the design, Polyalphaolefin (PAO) particles were generated inside the hood, and leakage was measured every 10 s for 90 s. The open side of the hood was divided into nine sections for consistent leakage measurements, and a standardized structure was implemented to ensure accuracy. Our target was to maintain a leakage rate of less than 0.3%, in line with established filter-testing criteria. Through iterative improvements based on leakage rates and intubation efficiency, we achieved significant results. Despite reducing the hood's size, the redesigned enclosure showed a 36.2% reduction in leakage rates and an approximately 3204.6% increase in aerosol extraction efficiency in simulations. The modified hood, even in an open configuration, maintained a droplet leakage rate of less than 0.3%. These findings demonstrate the potential of a CFD-guided design in developing respiratory barriers that effectively reduce aerosol transmission risks during high-risk medical procedures. This approach not only improves the safety of both patients and healthcare providers but also provides a scalable solution for safer execution of AGPs in various healthcare settings.