COVID-19 virus released from larynx might cause a higher exposure dose in indoor environment

Wu, Jen Leih; Weng, Wenguo

doi:10.1016/j.envres.2021.111361

Cited by 29 publications

(11 citation statements)

References 53 publications

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“…Since body shapes could significantly affect the contamination transport 19 with movement, human‐shape models were used in this study. The source person (SP) was a breathing human with real shape and facial details obtained through CT scanning 35 . However, the facial detail of the SP model was rich and might lead to negative volume cells if used for multi‐person movements.…”

Section: Methodsmentioning

confidence: 99%

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Multi‐person movement‐induced airflow and the effects on virus‐laden expiratory droplet dispersion in indoor environments

Geng

et al. 2022

Indoor Air

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Since the outbreak of Coronavirus Disease 2019 , more than 500 million people have been infected by May 2022, causing severe health hazards and economic losses. 1 Many respiratory diseases (influenza, SARS, MERS, and COVID-19) can be transmitted by droplets and aerosols. 2,3 In poorly ventilated indoor environments, large droplets (>50 μm) tend to deposit in seconds to minutes, while small aerosols (<5-10 μm) can suspend for hours, posing a potential risk to susceptible persons. [4][5][6] Since nearly 80% of respiratory infections happen indoors, 7 epidemic control in indoor environments is essential. The transmission mechanisms of exhaled virus-laden droplets 8,9 in indoor environments (restaurants, 10 classrooms, 11 airliner cabins, 12 subway stations 13 ) have been investigated. Since virus concentration generally decreased with distance from the source, a safe distance of about 1.5-2.0 m was widely used. 4,14 In addition, exhaled jets might be locked at a certain height in thermal-stratification indoor environments, strengthening the disease transmission. 15,16 However, many studies only considered scenarios with fixed positions of people, while human movement could significantly change the indoor airflow field and the distribution of virus-laden droplets.The superposition of human-induced airflow and turbulence might

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Section: Methodsmentioning

confidence: 99%

“…The source person (SP) was a breathing human with real shape and facial details obtained through CT scanning. 35 However,…”

Section: Model Scenes and Mesh Generationmentioning

confidence: 99%

Multi‐person movement‐induced airflow and the effects on virus‐laden expiratory droplet dispersion in indoor environments

Geng

et al. 2022

Indoor Air

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“…Our model incorporates the spreading of aerosols from ‘infected’ agents [ 1 , 28 ] and the measurement of exposure accumulated by the agents in the system. The concentration of aerosols c ( r , t ) follows the, diffusion equation where we also have the source term S and sink term c / τ .…”

Section: Methodsmentioning

confidence: 99%

“…Our model incorporates the spreading of aerosols from 'infected' agents [1,28] and the measurement of exposure accumulated by the agents in the system. The concentration of aerosols…”

Section: Present Monte-carlo Modelmentioning

confidence: 99%

Modelling aerosol-based exposure to SARS-CoV-2 by an agent based Monte Carlo method: Risk estimates in a shop and bar

et al. 2021

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Present day risk assessment on the spreading of airborne viruses is often based on the classical Wells-Riley model assuming immediate mixing of the aerosol into the studied environment. Here, we improve on this approach and the underlying assumptions by modeling the space-time dependency of the aerosol concentration via a transport equation with a dynamic source term introduced by the infected individual(s). In the present agent-based methodology, we study the viral aerosol inhalation exposure risk in two scenarios including a low/high risk scenario of a “supermarket”/“bar”. The model takes into account typical behavioral patterns for determining the rules of motion for the agents. We solve a diffusion model for aerosol concentration in the prescribed environments in order to account for local exposure to aerosol inhalation. We assess the infection risk using the Wells-Riley model formula using a space-time dependent aerosol concentration. The results are compared against the classical Wells-Riley model. The results indicate features that explain individual cases of high risk with repeated sampling of a heterogeneous environment occupied by non-equilibrium concentration clouds. An example is the relative frequency of cases that might be called superspreading events depending on the model parameters. A simple interpretation is that averages of infection risk are often misleading. They also point out and explain the qualitative and quantitative difference between the two cases—shopping is typically safer for a single individual person.

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“…e study has shown that the transmission of SARS-CoV-2 could be generated through respiratory droplets and small aerosols [1]. is has led to extensive research on infections and infection control in both outdoor and indoor environments [2][3][4][5][6]. A logical solution to minimizing disease transmission was the isolation of the infected patient.…”

Section: Introductionmentioning

confidence: 99%

A CFD Study on the Design Optimization of Airborne Infection Isolation Room

Nguyen

Kieu

2022

Mathematical Problems in Engineering

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Airborne infection isolation (AII) rooms are used to accommodate patients with highly infectious diseases and keep the released pathogens to limit the risk of cross-infection. This paper proposes a concept for an AII room made from two shipping containers to handle the scarcity of hospital beds when the COVID-19 disease spreads over the world. The proposed system consists of the main isolation room, anteroom, and toilet as well as other functional areas. In addition, the main isolation room was modeled with important components such as a supply air vent, exhaust air, a patient, and a bed. The computational fluid dynamics (CFD) approach based on the finite volume method (FVM) is used to solve the three-dimensional governing equations. The CO2 concentration was used to determine the infectious contaminant concentration of the air in the room. Therefore, the infectious control could be evaluated by the air change per hour (ACH). The numerical results show that the room temperature is maintained at 24°C, which is appropriate for people in the room. The laminar airflow extends downward to the floor after leaving the supply air vent on the ceiling, creating circulating patterns throughout the room. When evaluating the effectiveness of ventilation systems to remove airborne contaminants based on different ACH numbers, the CO2 concentration in the room was reduced to 581 ppm, 477 ppm, and 438 ppm in the cases of 12 ACH, 24 ACH, and 48 ACH, respectively. As a result, the greater the number of air change per hour, the greater the performance for contaminant removal. It served as the foundation for assessing and optimizing the ventilation system of the portable negative pressure room.

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COVID-19 virus released from larynx might cause a higher exposure dose in indoor environment

Cited by 29 publications

References 53 publications

Multi‐person movement‐induced airflow and the effects on virus‐laden expiratory droplet dispersion in indoor environments

Multi‐person movement‐induced airflow and the effects on virus‐laden expiratory droplet dispersion in indoor environments

Modelling aerosol-based exposure to SARS-CoV-2 by an agent based Monte Carlo method: Risk estimates in a shop and bar

A CFD Study on the Design Optimization of Airborne Infection Isolation Room

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