Reducing aerosol dispersion by High Flow Therapy in COVID-19: High Resolution Computational Fluid Dynamics Simulations of Particle Behavior during High Velocity Nasal Insufflation with a Simple Surgical Mask.

Objective: All respiratory care represents some risk of becoming an Aerosol Generating Procedure (AGP) during COVID-19 patient management. Personal Protective Equipment (PPE) and Environmental Control/Engineering is advised. High Velocity Nasal Insufflation (HVNI) and High Flow Nasal Cannula (HFNC) deliver High Flow Oxygen (HFO) therapy, established as a competent means of supporting oxygenation for acute respiratory distress patients, including that precipitated by COVID-19. Although unlikely to present a disproportionate particle dispersal risk, AGP from HFO continues to be a concern. Previously, we published a preliminary model. Here, we present a subsequent high-resolution simulation (higher complexity/reliability) to provide a more accurate and precise particle characterization on the effect of surgical masks on patients during HVNI, Low-Flow Oxygen therapy (LFO2), and tidal breathing.

Methods: This in-silico modeling study of HVNI, LFO2, and tidal breathing presents ANSYS Fluent Computational Fluid Dynamics simulations that evaluate the effect of Type I surgical mask use over patient face on particle/droplet behavior.

Results: This in-silico modeling simulation study of HVNI (40L∙min-1 ) with a simulated surgical mask suggests 88.8% capture of exhaled particulate mass in the mask, compared to 77.4% in LFO2 (6L∙min-1 ) capture, with particle distribution escaping to the room (>1m from face) lower for HVNI+Mask versus LFO2+Mask (8.23% versus 17.2%). The overwhelming proportion of particulate escape was associated with mask-fit designed model gaps. Particle dispersion was associated with lower velocity.

Conclusions: These simulations suggest employing a surgical mask over the HVNI interface may be useful in reduction of particulate mass distribution associated with AGPs.This article is protected by copyright. All rights reserved.