Fluid dynamics of respiratory droplets in the context of COVID-19: Airborne and surfaceborne transmissions

On the efficacy of facial masks to suppress the spreading of pathogen-carrying saliva particles during human respiratory events: Insights gained via high-fidelity numerical modeling

Respiratory fluid dynamics is integral to comprehending the transmission of infectious diseases and the effectiveness of interventions such as face masks and social distancing. In this research, we present our recent studies that investigate respiratory particle transport via high-fidelity large eddy simulation coupled with the Lagrangian particle tracking method. Based on our numerical simulation results for human respiratory events with and without face masks, we demonstrate that facial masks could significantly suppress particle spreading. The studied respiratory events include coughing and normal breathing through mouth and nose. Using the Lagrangian particle tracking simulation results, we elucidated the transport pathways of saliva particles during inhalation and exhalation of breathing cycles, contributing to our understanding of respiratory physiology and potential disease transmission routes. Our findings underscore the importance of respiratory fluid dynamics research in informing public health strategies to reduce the spread of respiratory infections. Combining advanced mathematical modeling techniques with experimental data will help future research on airborne disease transmission dynamics and the effectiveness of preventive measures such as face masks.

Building parameters linked with indoor transmission of SARS-CoV-2

The rapid spread of Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has emphasized the importance of understanding and adapting to the indoor remediation of transmissible diseases to decrease the risk for future pandemic threats. While there were many precautions in place to hinder the spread of COVID-19, there has also been a substantial increase of new research on SARS-CoV-2 that can be utilized to further mitigate the transmission risk of this novel virus. This review paper aims to identify the building parameters of indoor spaces that could have considerable influence on the transmission of SARS-CoV-2. The following building parameters have been identified and analyzed, emphasizing their link with the indoor transmission of SARS-CoV-2: temperature and relative humidity, temperature differences between rooms, ventilation rate and access to natural ventilation, occupant density, surface type and finish, airflow direction and speed, air stability, indoor air pollution, central air conditioning systems, capacity of air handling system and HVAC filter efficiency, edge sealing of air filters, room layout and interior design, and compartmentalization of interior space. This paper also explains the interactions of SARS-CoV-2 with indoor environments and its persistence. Furthermore, the modifications of the key building parameters have been discussed for controlling the transmission of SARS-CoV-2 in indoor spaces. Understanding the information provided in this paper is crucial to develop effective health and safety measures that will aid in infection prevention.

Modeling virus transport and dynamics in viscous flow medium

In this paper, we developed a mathematical model to simulate virus transport through a viscous background flow driven by the natural pumping mechanism. Two types of respiratory pathogens viruses (SARS-Cov-2 and Influenza-A) are considered in this model. The Eulerian-Lagrangian approach is adopted to examine the virus spread in axial and transverse directions. The Basset-Boussinesq-Oseen equation is considered to study the effects of gravity, virtual mass, Basset force, and drag forces on the viruses transport velocity. The results indicate that forces acting on the spherical and non-spherical particles during the motion play a significant role in the transmission process of the viruses. It is observed that high viscosity is responsible for slowing the virus transport dynamics. Small sizes of viruses are found to be highly dangerous and propagate rapidly through the blood vessels. Furthermore, the present mathematical model can help to better understand the viruses spread dynamics in a blood flow.

Factors Associated with Job Stress and Their Effects on Mental Health among Nurses in COVID-19 Wards in Four Hospitals in Korea

Increased workload during the COVID-19 pandemic has threatened nurses' mental health. This study aimed to identify factors associated with job stress in COVID-19 nurses compared to other nurses. Nurses were recruited from four hospitals in Republic of Korea in November 2020. The general sociodemographic questionnaire, job stress, anxiety (GAD-7), and depression (PHQ-9) were used to conduct an online survey. Stepwise multiple regression analysis was used to identify the factors associated with job stress. A total of 290 participants were analyzed: 122 in the dedicated ward and 168 in the nondedicated ward nurse groups. Job stress, anxiety, and depression were higher in nurses dedicated to COVID-19 (4.19 ± 0.59, 5.98 ± 3.92, and 6.97 ± 4.47, respectively) than in the nondedicated group (3.92 ± 0.72 (p = 0.001), 4.98 ± 4.20 (p = 0.042), and 5.92 ± 4.36 (p = 0.047), respectively). Among COVID-19 nurses, job stress levels were higher in 30-39 year olds than in 20-29 year olds (3.71 ± 0.43 vs. 4.04 ± 0.54, p = 0.006) and in non-smokers compared with smokers (3.85 ± 0.49 vs. 3.38 ± 0.53, p = 0.24). Anxiety (β = 0.34, standard error (SE) = 0.01, p < 0.001) and clinical experience of 5-10 years (β = 0.23, SE = 0.10, p = 0.004) were associated with job stress. These findings can be applied when devising response strategies for infectious diseases and developing psychological and organizational intervention programs for alleviating job stress in nurses.

Influence of indoor environmental conditions on airborne transmission and lifetime of sneeze droplets in a confined space: a way to reduce COVID-19 spread

Effects of indoor temperature (T∞) and relative humidity (RH∞) on the airborne transmission of sneeze droplets in a confined space were studied over the T∞ range of 15-30 °C and RH∞ of 22-62%. In addition, a theoretical evaporation model was used to estimate the droplet lifetime based on experimental data. The results showed that the body mass index (BMI) of the participants played an important role in the sneezing jet velocity, while the impact of the BMI and gender of participants was insignificant on the size distribution of droplets. At a critical relative humidity RH∞,crit of 46%, the sneezing jet velocity and droplet lifetime were roughly independent of T∞. At RH∞ < RH∞,crit, the sneezing jet velocity decreased by increasing T∞ from 15 to 30 °C, while its trend was reversed at RH∞ > RH∞,crit. The maximum spreading distance of aerosols increased by decreasing the RH∞ and increasing T∞, while the droplet lifetime increased by decreasing T∞ at RH∞ > RH∞,crit. The mean diameter of aerosolized droplets was less affected by T∞ than the large droplets at RH∞ < RH∞,crit, while the mean diameter and number fraction of aerosols were more influenced by RH∞ than the T∞ in the range of 46% ≤ RH∞ ≤ 62%. In summary, this study suggests suitable indoor environmental conditions by considering the transmission rate and lifetime of respiratory droplets to reduce the spread of COVID-19.

Effect of indoor temperature on the velocity fields and airborne transmission of sneeze droplets: An experimental study and transient CFD modeling

The spread of the COVID-19 pandemic through the airborne transmission of coronavirus-containing droplets emitted during coughing, sneezing, and speaking has now been well recognized. This study presented the effect of indoor temperature (T∞) on the airflow dynamics, velocity fields, size distribution, and airborne transmission of sneeze droplets in a confined space through experimental investigation and computational fluid dynamic (CFD) modeling. The CFD simulations were performed using the renormalization group k-ε turbulence model. The experimental shadowgraph imaging and CFD simulations showed the time evolution of sneeze droplet concentrations into the turbulent expanded puff, droplet cloud, and fully-dispersed droplets. Also, the predicted mean velocity of droplets was compared with the obtained experimental data to assess the accuracy of the results. In addition, the validated computational model was used to study the sneeze complex airflow behavior and airborne transmission of small, medium, and large respiratory droplets in confined spaces at different temperatures. The warm room showed more than ∼14 % increase in airborne aerosols than the room with a mild temperature. The study provides information on the effect of room temperature on the evaporation of respiratory droplets during sneezing. The findings of this fundamental study may be used in developing exposure guidelines by controlling the temperature level in indoor environments to reduce the exposure risk of COVID-19.

Prediction of respiratory droplets evolution for safer academic facilities planning amid COVID-19 and future pandemics: A numerical approach

Airborne dispersion of the novel SARS-CoV-2 through the droplets produced during expiratory activities is one of the main transmission mechanisms of this virus from one person to another. Understanding how these droplets spread when infected humans with COVID-19 or other airborne infectious diseases breathe, cough or sneeze is essential for improving prevention strategies in academic facilities. This work aims to assess the transport and fate of droplets in indoor environments using Computational Fluid Dynamics (CFD). This study employs unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations with the Euler-Lagrange approach to visualize the location of thousands of droplets released in a respiratory event and their size evolution. Furthermore, we assess the dispersion of coughing, sneezing, and breathing saliva droplets from an infected source in a classroom with air conditioning and multiple occupants. The results indicate that the suggested social distancing protocol is not enough to avoid the transmission of COVID-19 since small saliva droplets ( ≤ 12 μm) can travel in the streamwise direction up to 4 m when an infected person coughs and more than 7 m when sneezes. These droplets can reach those distances even when there is no airflow from the wind or ventilation systems. The number of airborne droplets in locations close to the respiratory system of a healthy person increases when the relative humidity of the indoor environment is low. This work sets an accurate, rapid, and validated numerical framework reproducible for various indoor environments integrating qualitative and quantitative data analysis of the droplet size evolution of respiratory events for a safer design of physical distancing standards and air cleaning technologies.

The effect of relative air humidity on the evaporation timescales of a human sneeze

The present paper investigates droplet and aerosol emission from the human respiratory function by numerical and experimental methods, which is analyzed at the worst-case scenario, a violent sneeze without a face covering. The research findings develop the understanding of airborne disease transmission relevant to COVID-19, its recent variants, and other airborne pathogens. A human sneeze is studied using a multiphase Computational Fluid Dynamics (CFD) model using detached eddy simulation coupled to the emission of droplets that break up, evaporate, and disperse. The model provides one of the first experimental benchmarks of CFD predictions of a human sneeze event. The experiments optically capture aerosols and droplets and are processed to provide spatiotemporal data to validate the CFD model. Under the context of large random uncertainty, the studies indicate the reasonable correlation of CFD prediction with experimental measurements using velocity profiles and exposure levels, indicating that the model captures the salient details relevant to pathogen dispersion. Second, the CFD model was extended to study the effect of relative humidity with respect to the Wells curve, providing additional insight into the complexities of evaporation and sedimentation characteristics in the context of turbulent and elevated humidity conditions associated with the sneeze. The CFD results indicated correlation with the Wells curve with additional insight into features, leading to non-conservative aspects associated with increased suspension time. These factors are found to be associated with the combination of evaporation and fluid-structure-induced suspension. This effect is studied for various ambient air humidity levels and peaks for lower humidity levels, indicating that the Wells curve may need a buffer in dry climates. Specifically, we find that the increased risk in dry climates may be up to 50% higher than would be predicted using the underlying assumptions in Wells' model.

Evaporation of liquid nanofilms: A minireview

Evaporation of virus-loaded droplets and liquid nanofilms plays a significant role in the pandemic of COVID-19. The evaporation mechanism of liquid nanofilms has attracted much attention in recent decades. In this minireview, we first introduce the relationship between the evaporation process of liquid nanofilms and the pandemic of COVID-19. Then, we briefly provide the frontiers of liquid droplet/nanofilm evaporation on solid surfaces. In addition, we discuss the potential application of machine learning in liquid nanofilm evaporation studies, which is expected to be helpful to build up a more accurate molecular model and to investigate the evaporation mechanism of liquid nanofilms on solid surfaces.

High-resolution large-eddy simulation of indoor turbulence and its effect on airborne transmission of respiratory pathogens-Model validation and infection probability analysis

High-resolution large-eddy simulation (LES) is exploited to study indoor air turbulence and its effect on the dispersion of respiratory virus-laden aerosols and subsequent transmission risks. The LES modeling is carried out with unprecedented accuracy and subsequent analysis with novel mathematical robustness. To substantiate the physical relevance of the LES model under realistic ventilation conditions, a set of experimental aerosol concentration measurements are carried out, and their results are used to successfully validate the LES model results. The obtained LES dispersion results are subjected to pathogen exposure and infection probability analysis in accordance with the Wells-Riley model, which is here mathematically extended to rely on LES-based space- and time-dependent concentration fields. The methodology is applied to assess two dissimilar approaches to reduce transmission risks: a strategy to augment the indoor ventilation capacity with portable air purifiers and a strategy to utilize partitioning by exploiting portable space dividers. The LES results show that use of air purifiers leads to greater reduction in absolute risks compared to the analytical Wells-Riley model, which fails to predict the original risk level. However, the two models do agree on the relative risk reduction. The spatial partitioning strategy is demonstrated to have an undesirable effect when employed without other measures, but may yield desirable outcomes with targeted air purifier units. The study highlights the importance of employing accurate indoor turbulence modeling when evaluating different risk-reduction strategies.

An integrated simulation framework for the prevention and mitigation of pandemics caused by airborne pathogens

In this work, we developed an integrated simulation framework for pandemic prevention and mitigation of pandemics caused by airborne pathogens, incorporating three sub-models, namely the spatial model, the mobility model, and the propagation model, to create a realistic simulation environment for the evaluation of the effectiveness of different countermeasures on the epidemic dynamics. The spatial model converts images of real cities obtained from Google Maps into undirected weighted graphs that capture the spatial arrangement of the streets utilized next for the mobility of individuals. The mobility model implements a stochastic agent-based approach, developed to assign specific routes to individuals moving in the city, through the use of stochastic processes, utilizing the weights of the underlying graph to deploy shortest path algorithms. The propagation model implements both the epidemiological model and the physical substance of the transmission of an airborne pathogen (in our approach, we investigate the transmission parameters of SARS-CoV-2). The deployment of a set of countermeasures was investigated in reducing the spread of the pathogen, where, through a series of repetitive simulation experiments, we evaluated the effectiveness of each countermeasure in pandemic prevention.

Large eddy simulation of cough jet dynamics, droplet transport, and inhalability over a ten minute exposure

High fidelity simulations of expiratory events such as coughing provide the opportunity to predict the fate of the droplets from the turbulent jet cloud produced from a cough. It is well established that droplets carrying infectious pathogens with diameters of 1 - 5   μ m remain suspended in the air for several hours and transported by the air currents over considerable distances (e.g., in meters). This study used a highly resolved mesh to capture the multiphase turbulent buoyant cloud with suspended droplets produced by a cough. The cough droplets' dispersion was subjected to thermal gradients and evaporation and allowed to disperse between two humans standing 2 m apart. A nasal cavity anatomy was included inside the second human to determine the inhaled droplets. Three diameter ranges characterized the droplet cloud, < 5   μ m , which made up 93% of all droplets by number; 5 to 100 μm comprised 3%, and > 100   μ m comprising 4%. The results demonstrated the temporal evolution of the cough event, where a jet is first formed, followed by a thermally driven puff cloud with the latter primarily composed of droplets under 5 μm diameter, moving with a vortex string structure. After the initial cough, the data were interpolated onto a more coarse mesh to allow the simulation to cover ten minutes, equivalent to 150 breathing cycles. We observe that the critical diameter size susceptible to inhalation was 0.5   μ m , although most inhaled droplets after 10 min by the second human were approximately 0.8   μ m . These observations offer insight into the risk of airborne transmission and numerical metrics for modeling and risk assessment.

Numerical investigation of droplets in a cross-ventilated space with sitting passengers under asymptomatic virus transmission conditions

Asymptomatic virus transmission in public transportation is a complex process that is difficult to analyze computationally and experimentally. We present a high-resolution computational study for investigating droplet dynamics under a speech-like exhalation mode. A large eddy simulation coupled with Lagrangian tracking of drops was used to model a rectangular space with sitting thermal bodies and cross-ventilated with a multislot diffuser. Release of drops from different seat positions was evaluated to analyze the decontamination performance of the ventilation system. The results showed an overall good performance, with an average of 24.1% of droplets removed through the exhaust in the first 40 s. The droplets' distribution revealed that higher concentrations were less prevalent along the center of the domain where the passengers sit. Longitudinal contamination between rows was noted, which is a negative aspect for containing the risk of infection in a given row but has the benefit of diluting the concentration of infectious droplets. Droplets from the window seat raised more vertically and invaded the space of other passengers to a lesser extent. In contrast, droplets released from the middle seat contaminated more the aisle passenger's space, indicating that downward flow from personal ventilation could move down droplets to its breathing region. Droplets released from the aisle were dragged down by the ventilation system immediately. The distance of drops to the mouth of the passengers showed that the majority passed at a relatively safe distance. However, a few of them passed at a close distance of the order of magnitude of 1 cm.

Evaluating a transparent coating on a face shield for repelling airborne respiratory droplets

A face shield is an important personal protective equipment to avoid the airborne transmission of COVID-19. We assess a transparent coating on a face shield that repels airborne respiratory droplets to mitigate the spread of COVID-19. The surface of the available face shield is hydrophilic and exhibits high contact angle hysteresis. The impacting droplets stick on it, resulting in an enhanced risk of fomite transmission of the disease. Further, it may get wetted in the rain, and moisture may condense on it in the presence of large humidity, which may blur the user's vision. Therefore, the present study aims to improve the effectiveness of a face shield. Our measurements demonstrate that the face shield, coated by silica nanoparticles solution, becomes superhydrophobic and results in a nominal hysteresis to the underlying surface. We employ high-speed visualization to record the impact dynamics of microliter droplets with a varying impact velocity and angle of attack on coated and non-coated surfaces. While the droplet on non-coated surface sticks to it, in the coated surface the droplets bounce off and roll down the surface, for a wide range of Weber number. We develop an analytical model and present a regime map of the bouncing and non-bouncing events, parametrized with respect to the wettability, hysteresis of the surface, and the Weber number. The present measurements provide the fundamental insights of the bouncing droplet impact dynamics and show that the coated face shield is potentially more effective in suppressing the airborne and fomite transmission.