Open Collections

Abstract

The risk of airborne disease transmission in hospital rooms during aerosol-generating medical procedures (AGMPs) is influenced by ventilation design, room layout, and occupant activity. However, quantitative recommendations for ventilation parameters are scarce. Moreover, room layout and occupant activity parameters are often omitted from studies due to computational budget constraints. As a result, the development of policies and technologies aimed at mitigating airborne disease transmission has been limited. This dissertation focuses on three sub-objectives: (1) defining the input parameters and boundary conditions needed for clinically-relevant AGMP simulations; (2) developing an open-source large-eddy simulation (LES) software capable of modeling the parameters defined in objective 1; (3) conducting a fractional-factorial study using the software from objective 2 to quantify the relative influence of parameters defined in objective 1. To characterize existing ventilation, room layout, and occupancy parameters in hospital rooms where AGMPs occur, survey responses from 38 healthcare workers and hospital drawing packages from 37 hospitals are reviewed. Descriptive statistics for parameters such as ventilation rate, supply inlet area, occupant movement speed, and many more are available in this dissertation. Values from these intervals act as a guide when choosing boundary and initial conditions for AGMP simulations. A Toolbox fOr Simulating Ventilation and Aerosols (TOSVA) is an open-source LES code developed as part of this dissertation. TOSVA is capable of simulating human activity, particle concentrations, and infection probability in indoor spaces. TOSVA uses a quadrature method of moments for the particulate phase with a Runge-Kutta solution scheme and product differencing correction step, reducing computational resource requirements compared to discrete phase particle modelling. Simulation results from TOSVA are validated against previous experiments and simulations as part of this dissertation. Using TOSVA, a fractional-factorial study is conducted to quantify the relative influence of ventilation rate, exhaust location, room pressure design, furniture/equipment locations, occupant movement, supply inlet turbulence, respiratory support, and procedure time on infection probability. Values for each input variable are chosen based on results from the survey and hospital drawings review. Overall, the software developed as part of this dissertation is a very useful tool for predicting aerosol dispersion and infection risk.