An Efficient Ventilation Configuration for Preventing Bioaerosol Exposures to Health Care Workers in Airborne Infection Isolation Rooms

An efficient ventilation configuration of an airborne infection isolation room (AIIR) is essential for protecting Health care workers (HCW) from exposure to potentially-infectious patient aerosol. This paper presents a Computational Fluid Dynamics (CFD) study to predict airflow distribution patterns throughout the AIIR and the bioaerosol dispersal originiating from an infectious patient for a range of AIIR ventilation configuration design considerations. In the present study with ventilation configuration 1, the AIIR has two supply vents and 1 exhaust grille corresponding to that of a traditional ceiling mounted ventilation arrangement observed in existing hospitals. Alternate ventilation configuration 2 retains the linear supply diffuser in ventilation configuration 1 but interchanges the Square supply and Main Exhaust locations. The direct-control exhaust configuration evaluated in this study has the ceiling exhaust replaced with vented patient headboard mantle and canopy arrangement, while the supply diffusers locations remains the same as configuration 2. Furthermore, the effects of shifting the HCW’s location on the room air distribution and the bioaerosol dispersal behavior is studied to ensure whether the Direct-Control exhaust configuration is efficient in protecting the HCW from patient’s contaminated air as the HCW standing near the patient’s bed shifts positions while carrying out cough generating procedures. The results show that the Direct-control exhaust configuration is the most efficient in preventing the patient’s contaminated air from entering the HCW’s region. Further evaluation of this configuration is recommended for potential adoption within new and existing AIIRs to reduce the potential impact of infectious epidemics on severe workforce absenteeism and our nation’s significant financial losses. INTRODUCTION Many highly infectious agents such as SARS, Influenza, MERS-CoV Tuberculosis, and Ebola hemorrhagic fever (CDC Report 2015) are spread by airborne or droplet transmission in health-care settings [Assiri A (2013)]. There are about 12.6 million personnel designated as healthcare workers (HCWs) by the Bureau of Labor Statistics. HCWs providing direct patient care services are at high risk for occupational transmission of airborne infections [Zumla A (2014), Marchand et al., (2016), Petti S (2016)]. To protect HCWs from potential airborne exposures, the design of proper ventilation arrangements in an AIIR are strictly essential and pressurization is a critical contamination control strategy at the room boundary. Furthermore, airflow pattern (direction) and air change rate (dilution) are critical contamination strategies within a room. Relevance to ASHRAE 2017 ASHRAE Annual Conference—Papers © U.S. Government 1 LB-17-C005 This file is licensed to ASHRAE Member (member@ashrae.org). This download was made available with support from Rittal. Copyright ASHRAE 2020. METHODS The transient, 3-D, incompressible Navier-stokes equations, including gravity, were solved with pressurevelocity coupling achieved using the Semi-Implicit Pressure-Linked equations (SIMPLE) algorithm. The energy equation was also solved to account for temperature variations. The transport equations were discretized using a second-order upwind scheme with second-order implicit discretization for the temporal terms. Turbulence was modeled using the realizable k-ε model. Numerical analysis was performed using the commercial CFD code FLUENT based on the finite volume method. Over each control volume, the SIMPLE algorithm was used to iteratively solve for these Governing equations. The steady-state flow field in the AIIR was determined before the patient’s coughing and HCW’s breathing were initiated. The Convergence criteria for the steady state flow field were set at 10-4 for all equations. Next, the patient cough cycle consisted of a mixture of cough aerosol and air for a 0.5 seconds cough cycle. The Lagrangian discrete-phase model in the finite-volume solver ANSYS Fluent 17.0 was used to track infectious bio aerosols within the AIIR. O’Rourke’s stochastic algorithm was used to model droplet collision, and the Taylor analogy breakup (TAB) model was used for droplet breakup using CFD modeling program. The patient coughed for the time period of 0.5 seconds while the HCW continued breathing. At the end of the patient’s cough cycle [Gupta 2008], the patient resumed normal breathing cycle of 4 seconds [Guyton and Hall 2011] and the cough aerosols dispersal throughout mock AIIR were tracked in time until all these aerosols were exhausted from the room by the exhaust ventilation or through bathroom door gaps.