Current and potential approaches on assessing airflow and particle dispersion in healthcare facilities: a systematic review

Abstract

An indoor environment in a hospital building requires a high indoor air quality (IAQ) to overcome patients’ risks of getting wound infections without interrupting the recovery process. However, several problems arose in obtaining a satisfactory IAQ, such as poor ventilation design strategies, insufficient air exchange, improper medical equipment placement and high door opening frequency. This paper presents an overview of various methods used for assessing the IAQ in hospital facilities, especially in an operating room, isolation room, anteroom, postoperative room, inpatient room and dentistry room. This review shows that both experimental and numerical methods demonstrated their advantages in the IAQ assessment. It was revealed that both airflow and particle tracking models could result in different particle dispersion predictions. The model selection should depend on the compatibility of the simulated result with the experimental measurement data. The primary and secondary forces affecting the characteristics of particle dispersion were also discussed in detail. The main contributing forces to the trajectory characteristics of a particle could be attributed to the gravitational force and drag force regardless of particle size. Meanwhile, the additional forces could be considered when there involves temperature gradient, intense light source, submicron particle, etc. The particle size concerned in a healthcare facility should be less than 20 μm as this particle size range showed a closer relationship with the virus load and a higher tendency to remain airborne. Also, further research opportunities that reflect a more realistic approach and improvement in the current assessment approach were proposed.

Ventilation Strategies for Mitigating Airborne Infections in Healthcare Facilities: A Mini-Review and Bibliometric Analysis (1970 to 2021)

“…Despite the broad application of the CFD approach, it could yet replace the experimental work as the measurement data is important for the validation of the numerical model. For accurate CFD modelling, the verification and validation steps on the selection of turbulence models, wall treatment function and the monitoring of residuals are still necessary to ensure the validity of results [114].…”

“…The size of cough-generated droplets was reported to be between 0.62 and 15.9 µm (average size 8.35 µm), but the distribution of particle sizes could be altered by the presence of viral infections [118]. According to a recent review, the particle size concerned in a healthcare facility should be less than 20 µm as this particle size range showed a closer relationship with the virus load and a higher tendency to remain airborne [114]. This is because the larger particle tends to deposit rapidly onto the surface while the small particle will remain airborne and travel over long distances for several hours [124].…”

A CFD assessment on ventilation strategies in mitigating healthcare-associated infection in single patient ward

“…In the present study, Grid Convergence Index (GCI) was calculated to evaluate the numerical error due to different sets of grid densities. GCI is a relative error bound that describes the variation of solutions with mesh refinement [31]. Volk et al claimed a GCI value of less than 10 % could be considered acceptable [32].…”

Indoor Air Quality and Comfort in Native American Shelters: Simulation and Actual Data Analysis

“…Furthermore, the EnergyPlus engine has been used in previous articles to evaluate the energy performance of Native American shelters [9]. In addition to this, Design-Builder's simulation process has been validated using the Building Energy Simulation Test (BESTest), which the American Department of Energy recognizes to evaluate building energy simulation across program features [10], [11]. Scientific articles incorporated in the literature review were written by other authors who have investigated the criteria to clarify errors that commonly occur in these models and standardize the calibration process of modelling a building [12], [13].…”