ABSTRACT
To quantify the risk of the transmission of respiratory infections in indoor environments, we systematically assessed exposure to talking- and breathing-generated respiratory droplets in a generic indoor environment using computational fluid dynamic (CFD) simulations. The flow field in the indoor environment was obtained with SST k-ω model and Lagrangian method was used to predict droplet trajectories, where droplet evaporation was considered. Droplets can be categorized into small droplets (initial size ≤30 μm or ≤10 μm as droplet nuclei), medium droplets (30–80 μm) and large droplets (>100 μm) according to the exposure characteristics. Droplets up to 100 μm, particular the small ones, can contribute to both short-range and long-range airborne routes. For the face-to-face talking scenario, the intake fraction and deposition fractions of droplets on the face and facial mucosa of the susceptible were up to 4.96%, 2.14%, and 0.12%, respectively, indicating inhalation is the dominant route. The exposure risk from a talking infector decreases monotonically with the interpersonal distance, while that of nasal-breathing generated droplets maintains a relatively stable level within 1.0 m. Keeping an angle of 15° or above with the expiratory flow is efficient to reduce intake fractions to <0.37% for small droplets. Adjusting the orientation from face-to-face to face-to-back can reduce exposure to small droplets by approximately 88.0% during talking and 66.2% during breathing. A higher ventilation rate can reduce the risk of exposure to small droplets but may increase the risk of transmission via medium droplets by enhancing their evaporation rate. This study would serve as a fundamental research for epidemiologist, healthcare workers and the public in the purpose of infection control. © 2023 Elsevier Ltd
ABSTRACT
To quantify the risk of the transmission of respiratory infections in indoor environments, we systematically assessed exposure to talking- and breathing-generated respiratory droplets in a generic indoor environment using computational fluid dynamic (CFD) simulations. The flow field in the indoor environment was obtained with SST k-ω model and Lagrangian method was used to predict droplet trajectories, where droplet evaporation was considered. Droplets can be categorized into small droplets (initial size ≤30 μm or ≤10 μm as droplet nuclei), medium droplets (30–80 μm) and large droplets (>100 μm) according to the exposure characteristics. Droplets up to 100 μm, particular the small ones, can contribute to both short-range and long-range airborne routes. For the face-to-face talking scenario, the intake fraction and deposition fractions of droplets on the face and facial mucosa of the susceptible were up to 4.96%, 2.14%, and 0.12%, respectively, indicating inhalation is the dominant route. The exposure risk from a talking infector decreases monotonically with the interpersonal distance, while that of nasal-breathing generated droplets maintains a relatively stable level within 1.0 m. Keeping an angle of 15° or above with the expiratory flow is efficient to reduce intake fractions to <0.37% for small droplets. Adjusting the orientation from face-to-face to face-to-back can reduce exposure to small droplets by approximately 88.0% during talking and 66.2% during breathing. A higher ventilation rate can reduce the risk of exposure to small droplets but may increase the risk of transmission via medium droplets by enhancing their evaporation rate. This study would serve as a fundamental research for epidemiologist, healthcare workers and the public in the purpose of infection control.
ABSTRACT
The novel SARS-CoV-2 outbreak was declared as pandemic by the World Health Organization (WHO) on March 11, 2020. Understanding the airborne route of SARS-CoV-2 transmission is essential for infection prevention and control. In this study, a total of 107 indoor air samples (45 SARS-CoV-2, 62 bacteria, and fungi) were collected from different wards of the Hajar Hospital in Shahrekord, Iran. Simultaneously, bacterial and fungal samples were also collected from the ambient air of hospital yard. Overall, 6 positive air samples were detected in the infectious 1 and infectious 2 wards, intensive care unit (ICU), computed tomography (CT) scan, respiratory patients' clinic, and personal protective equipment (PPE) room. Also, airborne bacteria and fungi were simultaneously detected in the various wards of the hospital with concentrations ranging from 14 to 106 CFU m-3 and 18 to 141 CFU m-3, respectively. The highest mean concentrations of bacteria and fungi were observed in respiratory patients' clinics and ICU wards, respectively. Significant correlation (p < 0.05) was found between airborne bacterial concentration and the presence of SARS-CoV-2, while no significant correlation was found between fungi concentration and the virus presence. This study provided an additional evidence about the presence of SARS-CoV-2 in the indoor air of a hospital that admitted COVID-19 patients. Moreover, it was revealed that the monitoring of microbial quality of indoor air in such hospitals is very important, especially during the COVID-19 pandemic, for controlling the nosocomial infections.