Modelling aerosol transport and virus exposure with numerical simulations in relation to SARS-CoV-2 transmission by inhalation indoors

A critical review of research methodologies for COVID-19 transmission in indoor built environment

The Coronavirus Disease 2019 (COVID-19) has caused massive losses for the global economy. Scholars have used different methods to study the transmission mode and influencing factors of the virus to find effective methods to provide people with a healthy built environment. However, these studies arrived at different or even contradictory conclusions. This review presents the main research methodologies utilized in this field, summarizes the main investigation methods, and critically discusses their related conclusions. Data statistical analysis, sample collection, simulation models, and replication transmission scenarios are the main research methods. The summarized conclusion for prevention from all reviewed papers are: adequate ventilation and proper location of return air vents, proper use of personal protective equipment, as well as the reasonable and strict enforcement of policies are the main methods for reducing the transmission. Recommendations including standardized databases, causation clarification, rigorous experiment design, improved simulation accuracy and verification are provided.

Superspreading of SARS-CoV-2 at a choir rehearsal in Finland-A computational fluid dynamics view on aerosol transmission and patient interviews

INTRODUCTION

COVID-19 pandemic has highlighted the role of aerosol transmission and the importance of superspreading events. We analyzed a choir rehearsal in November 2020, where all participants, except one who had recently earlier recovered from COVID-19, were infected. We explore the risk factors for severe disease in this event and model the aerosol dispersion in the rehearsal room.

MATERIALS AND METHODS

Characteristics of participants were collected by interviews and supplemented with patient records. A computational simulation of aerosol distribution in the rehearsal room and the efficacy of potential safety measures was conducted using the Large-Eddy Simulation approach. Infection risk was studied by analyzing quanta emission and exposure with the Wells-Riley equation.

RESULTS

The simulation showed that airborne transmission likely explains this mass contagion event. Every singer was exposed to the virus in only 5 min from the beginning of the rehearsal, and maximum concentration levels were reached at 20 min the concentration levels started to approach a steady state after 20 min. Although concentration differences existed in the room, risk levels near (1 m) and far (5 m) from the aerosol source were similar for certain singers. Modeling indicated infection risk levels of 70-100% after one hour; the risk would have been considerably reduced by wearing high-filtration respirators. Age and pre-existing comorbidities predicted more severe disease. The high incidence of illness may be partly attributed to the relatively high median age of individuals. Additionally, those admitted to the hospital had multiple underlying health conditions that predispose them to more severe disease.

CONCLUSIONS

Airborne transmission and indoor space can explain this mass exposure event. High-filtration respirators could have prevented some infections. The importance of safety distances diminishes the longer the indoor event. The concept of safety distance is challenging, as our study suggests that long range airborne transmission may occur in indoor events with extended duration. We encourage informing the public, especially persons at risk, of safety measures during epidemics.

Estimation of the UV susceptibility of aerosolized SARS-CoV-2 to 254 nm irradiation using CFD-based room disinfection simulations

The recent COVID-19 pandemic has raised interest in efficient air disinfection solutions. The application of germicidal ultraviolet (GUV) irradiation is an excellent contender to prevent airborne transmission of COVID-19, as well as other existing and future infectious airborne diseases. While GUV has already been proven effective in inactivating SARS-CoV-2, quantitative data on UV susceptibility and dose requirements, needed to predict and optimize the performance of GUV solutions, is still limited. In this study, the UV susceptibility of aerosolized SARS-CoV-2 to 254 nm ultraviolet (UV) irradiation is investigated. This is done by employing 3D computational fluid dynamics based simulations of SARS-CoV-2 inactivation in a test chamber equipped with an upper-room UV-C luminaire and comparing the results to previously published measurements performed in the same test chamber. The UV susceptibility found in this study is (0.6 ± 0.2) m2/J, which is equivalent to a D90 dose between 3 and 6 J/m2. These values are in the same range as previous estimations based on other corona viruses and inactivation data reported in literature.

Estimated relative potential for airborne SARS-CoV-2 transmission in a day care centre

We estimated the hourly probability of airborne severe acute respiratory coronavirus 2 (SARS-CoV-2) transmission and further the estimated number of persons at transmission risk in a day care centre by calculating the inhaled dose for airborne pathogens based on their concentration, exposure time and activity. Information about the occupancy and activity of the rooms was collected from day care centre personnel and building characteristics were obtained from the design values. The generation rate of pathogens was calculated as a product of viral load of the respiratory fluids and the emission of the exhaled airborne particles, considering the prevalence of the disease and the activity of the individuals. A well-mixed model was used in the estimation of the concentration of pathogens in the air. The Wells-Riley model was used for infection probability. The approach presented in this study was utilised in the identification of hot spots and critical events in the day care centre. Large variation in the infection probabilities and estimated number of persons at transmission risk was observed when modelling a normal day at the centre. The estimated hourly infection probabilities between the worst hour in the worst room and the best hour in the best room varied in the ratio of 100:1. Similarly, the number of persons at transmission risk between the worst and best cases varied in the ratio 1000:1. Although there are uncertainties in the input values affecting the absolute risk estimates the model proved to be useful in ranking and identifying the hot spots and events in the building and implementing effective control measures.

Morocco's population contact matrices: A crowd dynamics-based approach using aggregated literature data

Estimation of contact patterns is often based on questionnaires and time-use data. The results obtained using these methods have been used extensively over the years and recently to predict the spread of the COVID-19 pandemic. They have also been used to test the effectiveness of non-pharmaceutical measures such as social distance. The latter is integrated into epidemiological models by multiplying contact matrices by control functions. We present a novel method that allows the integration of social distancing and other scenarios such as panic. Our method is based on a modified social force model. The model is calibrated using data relating to the movements of individuals and their interactions such as desired walking velocities and interpersonal distances as well as demographic data. We used the framework to assess contact patterns in different social contexts in Morocco. The estimated matrices are extremely assortative and exhibit patterns similar to those observed in other studies including the POLYMOD project. Our findings suggest social distancing would reduce the numbers of contacts by 95%. Further, we estimated the effect of panic on contact patterns, which indicated an increase in the number of contacts of 11%. This approach could be an alternative to questionnaire-based methods in the study of non-pharmaceutical measures and other specific scenarios such as rush hours. It also provides a substitute for estimating children's contact patterns which are typically assessed through parental proxy reporting in surveys.

The multi-dimensional challenges of controlling respiratory virus transmission in indoor spaces: Insights from the linkage of a microscopic pedestrian simulation and SARS-CoV-2 transmission model

SARS-CoV-2 transmission in indoor spaces, where most infection events occur, depends on the types and duration of human interactions, among others. Understanding how these human behaviours interface with virus characteristics to drive pathogen transmission and dictate the outcomes of non-pharmaceutical interventions is important for the informed and safe use of indoor spaces. To better understand these complex interactions, we developed the Pedestrian Dynamics-Virus Spread model (PeDViS), an individual-based model that combines pedestrian behaviour models with virus spread models incorporating direct and indirect transmission routes. We explored the relationships between virus exposure and the duration, distance, respiratory behaviour, and environment in which interactions between infected and uninfected individuals took place and compared this to benchmark 'at risk' interactions (1.5 metres for 15 minutes). When considering aerosol transmission, individuals adhering to distancing measures may be at risk due to the buildup of airborne virus in the environment when infected individuals spend prolonged time indoors. In our restaurant case, guests seated at tables near infected individuals were at limited risk of infection but could, particularly in poorly ventilated places, experience risks that surpass that of benchmark interactions. Combining interventions that target different transmission routes can aid in accumulating impact, for instance by combining ventilation with face masks. The impact of such combined interventions depends on the relative importance of transmission routes, which is hard to disentangle and highly context dependent. This uncertainty should be considered when assessing transmission risks upon different types of human interactions in indoor spaces. We illustrated the multi-dimensionality of indoor SARS-CoV-2 transmission that emerges from the interplay of human behaviour and the spread of respiratory viruses. A modelling strategy that incorporates this in risk assessments can help inform policy makers and citizens on the safe use of indoor spaces with varying inter-human interactions.

Review of the research status on the transmission and diffusion characteristics of indoor viral aerosol particles

This study reviews the generation and diffusion characteristics of indoor viral aerosol particles, numerical simulation methods for the diffusion process of viral aerosols, and related research on the impact mechanism of different ventilation methods on the diffusion process of viral aerosols. Research has shown that the selection of initial conditions such as exhalation mode, initial airflow velocity, particle size, turbulence model, and calculation method for the generation of aerosol particles by the human body is of great significance for the numerical simulation of the diffusion process of viral aerosol particles. At the same time, on the basis of selecting appropriate ventilation methods, the reasonable setting of ventilation parameters (temperature, speed, height, etc.) can effectively suppress the spread of viral aerosols. This study can provide a theoretical basis for the study of related respiratory diseases, as well as technical and theoretical support for the selection of indoor ventilation methods to reduce the risk of human exposure caused by viral aerosols in the construction field. It also provides guidance and reference for aerosol transport and environmental protection in indoor atmospheric environments.

Airborne respiratory aerosol transport and deposition in a two-person office using a novel diffusion-based numerical model

BACKGROUND

The COVID-19 pandemic was caused by the SARS-CoV-2 coronaviruses transmitted mainly through exposure to airborne respiratory droplets and aerosols carrying the virus.

OBJECTIVE

To assess the transport and dispersion of respiratory aerosols containing the SARS-CoV-2 virus and other viruses in a small office space using a diffusion-based computational modeling approach.

METHODS

A 3-D computational model was used to simulate the airflow inside the 70.2 m3 ventilated office. A novel diffusion model accounting for turbulence dispersion and gravitational sedimentation was utilized to predict droplet concentration transport and deposition. The numerical model was validated and used to investigate the influences of partition height and different ventilation rates on the concentration of respiratory aerosols of various sizes (1, 10, 20, and 50 µm) emitted by continuous speaking.

RESULTS

An increase in the hourly air change rate (ACH) from 2.0 to 5.6 decreased the 1 μm droplet concentration inside the office by a factor of 2.8 and in the breathing zone of the receptor occupant by a factor of 3.2. The concentration at the receptor breathing zone is estimated by the area-weighted average of a 1 m diameter circular disk, with its centroid at the center of the receptor mannequin mouth. While all aerosols were dispersed by airflow turbulence, the gravitational sedimentation significantly influenced the transport of larger aerosols in the room. The 1 and 10 μm aerosols remained suspended in the air and dispersed throughout the room. In contrast, the larger 20 and 50 μm aerosols deposited on the floor quickly due to the gravitational sedimentation. Increasing the partition between cubicles by 0.254 m (10") has little effect on the smaller aerosols and overall exposure.

IMPACT

This paper provides an efficient computational model for analyzing the concentration of different respiratory droplets and aerosols in an indoor environment. Thus, the approach could be used for assessing the influence of the spatial concentration variations on exposure for which the fully mixed model cannot be used.

Airborne pathogens diffusion: A comparison between tracer gas and pigmented aerosols for indoor environment analysis

The evaluation of airborne pathogens diffusion is a crucial practice in preventing airborne diseases like COVID-19, especially in indoor environments. Through this transmission route, pathogens can be carried by droplets, droplet nuclei and aerosols and be conveyed over long distances. Therefore, understanding their diffusion is vital for prevention and curbing disease transmission. There are different techniques used for this purpose, and one of the most common is the utilization of tracer gas, however, it has limitations such as the difference in size between the gas molecules and the respiratory droplets, as well as its incapability to take into account evaporation. For this reason, a new method for evaluating the diffusion of respiratory droplets has been developed. This approach involves the use of an ultrasonic emitter to release and disperse pigmented aerosols, and a colorimeter for the following quantitative evaluation. A comparison with the tracer gas technique has been carried out, showing for the pigmented aerosols methodology a response that is dependent on different relative humidity conditions, while there is no clear difference in the dispersion of tracer gas at high or low humidity.

Modeling the impact of distancing measures on infectious disease spread: a case study of COVID-19 in the Moroccan population

This paper explores the impact of various distancing measures on the spread of infectious diseases, focusing on the spread of COVID-19 in the Moroccan population as a case study. Contact matrices, generated through a social force model, capture population interactions within distinct activity locations and age groups. These matrices, tailored for each distancing scenario, have been incorporated into an SEIR model. The study models the region as a network of interconnected activity locations, enabling flexible analysis of the effects of different distancing measures within social contexts and between age groups. Additionally, the method assesses the influence of measures targeting potential superspreaders (i.e., agents with a very high contact rate) and explores the impact of inter-activity location flows, providing insights beyond scalar contact rates or survey-based contact matrices. The results suggest that implementing intra-activity location distancing measures significantly reduces in the number of infected individuals relative to the act of imposing restrictions on individuals with a high contact rate in each activity location. The combination of both measures proves more advantageous. On a regional scale, characterized as a network of interconnected activity locations, restrictions on the movement of individuals with high contact rates was found to result in a $ 2 \% $ reduction, while intra-activity location-based distancing measures was found to achieve a $ 44 \% $ reduction. The combination of these two measures yielded a $ 48\% $ reduction.

Early detection of new pandemic waves. Control chart and a new surveillance index

The COVID-19 pandemic highlights the pressing need for constant surveillance, updating of the response plan in post-peak periods and readiness for the possibility of new waves of the pandemic. A short initial period of steady rise in the number of new cases is sometimes followed by one of exponential growth. Systematic public health surveillance of the pandemic should signal an alert in the event of change in epidemic activity within the community to inform public health policy makers of the need to control a potential outbreak. The goal of this study is to improve infectious disease surveillance by complementing standardized metrics with a new surveillance metric to overcome some of their difficulties in capturing the changing dynamics of the pandemic. At statistically-founded threshold values, the new measure will trigger alert signals giving early warning of the onset of a new pandemic wave. We define a new index, the weighted cumulative incidence index, based on the daily new-case count. We model the infection spread rate at two levels, inside and outside homes, which explains the overdispersion observed in the data. The seasonal component of real data, due to the public surveillance system, is incorporated into the statistical analysis. Probabilistic analysis enables the construction of a Control Chart for monitoring index variability and setting automatic alert thresholds for new pandemic waves. Both the new index and the control chart have been implemented with the aid of a computational tool developed in R, and used daily by the Navarre Government (Spain) for virus propagation surveillance during post-peak periods. Automated monitoring generates daily reports showing the areas whose control charts issue an alert. The new index reacts sooner to data trend changes preluding new pandemic waves, than the standard surveillance index based on the 14-day notification rate of reported COVID-19 cases per 100,000 population.

Indoor Air Quality and COVID-19: A Scoping Review

Objectives: The COVID-19 pandemic has been a major public health concern for the past 3 years. Scientific evidence on the relationship between SARS-CoV-2 infection and indoor air quality still needs to be demonstrated. This scoping review aims to study the association between air quality indoors and COVID-19. Methods: A scoping review analyzing the association between indoor air quality and epidemiological outcomes was conducted. Papers published between 1 January 2020 and 31 October 2022 were included. Hospital settings were excluded from the study. Results: Eight relevant articles met the inclusion criteria. Indoor settings included workplaces, schools, restaurants, and public transport. Types of ventilation used to improve indoor air quality were dilution methods (opening windows) and mechanical systems with or without filtration or purifier. CO2 sensors were employed in one study. All the studies showed a positive association between indoor air quality and its improvement and epidemiological indicators. Conclusion: The findings of this scoping review indicate that indoor air quality, which can be improved with ventilation methods, may reduce the risk of developing COVID-19. Ventilation could thus be viewed as a possible effective mitigating method.

A review on sterilization methods of environmental decontamination to prevent the coronavirus SARS-CoV-2 (COVID-19 virus): A new challenge towards eco-friendly solutions

In recent years, the COVID-19 pandemic is currently wreaking havoc on the planet. SARS-CoV-2, the Severe Acute Respiratory Syndrome Coronavirus, is the current term for this outbreak. Reports about this novel coronavirus have been presented since the pandemic's breakout, and they have demonstrated that it transmits rapidly from person to person, primarily by droplets in the air. Findings have illustrated that SARS-CoV-2 can survive on surfaces from hours to days. Therefore, it is essential to find practical solutions to reduce the virus's impact on human health and the environment. This work evaluated common sterilization methods that can decontaminate the environment and items. The goal is that healthcare facilities, disease prevention organizations, and local communities can overcome the new challenge of finding eco-friendly solutions. Further, a foundation of information encompassing various sterilization procedures and highlighting their limits to choose the most appropriate method to stop disease-causing viruses in the new context has been presented. The findings of this crucial investigation contribute to gaining insight into the comprehensive sterilization approaches against the coronavirus for human health protection and sustainable environmental development.

On-site airborne pathogen detection for infection risk mitigation

Human-infecting pathogens that transmit through the air pose a significant threat to public health. As a prominent instance, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the COVID-19 pandemic has affected the world in an unprecedented manner over the past few years. Despite the dissipating pandemic gloom, the lessons we have learned in dealing with pathogen-laden aerosols should be thoroughly reviewed because the airborne transmission risk may have been grossly underestimated. From a bioanalytical chemistry perspective, on-site airborne pathogen detection can be an effective non-pharmaceutic intervention (NPI) strategy, with on-site airborne pathogen detection and early-stage infection risk evaluation reducing the spread of disease and enabling life-saving decisions to be made. In light of this, we summarize the recent advances in highly efficient pathogen-laden aerosol sampling approaches, bioanalytical sensing technologies, and the prospects for airborne pathogen exposure measurement and evidence-based transmission interventions. We also discuss open challenges facing general bioaerosols detection, such as handling complex aerosol samples, improving sensitivity for airborne pathogen quantification, and establishing a risk assessment system with high spatiotemporal resolution for mitigating airborne transmission risks. This review provides a multidisciplinary outlook for future opportunities to improve the on-site airborne pathogen detection techniques, thereby enhancing the preparedness for more on-site bioaerosols measurement scenarios, such as monitoring high-risk pathogens on airplanes, weaponized pathogen aerosols, influenza variants at the workplace, and pollutant correlated with sick building syndromes.

Optimizing indoor air quality: CFD simulation and novel air cleaning methods for effective aerosol particle inhibition in public spaces

In contemporary building ventilation, displacement and mixing ventilation demand high air volumes for rapid virus elimination, resulting in elevated energy consumption. To minimize the spread of viruses and decrease energy consumption for ventilation, this study employed CFD to explore the efficacy of a downward uniform flow field in impeding the transmission of aerosol particles in a high-traffic public facility, like a supermarket. The findings indicate that the downward uniform flow field proves insufficient when individuals remain static for extended periods. A wind speed of 0.1 m/s or higher becomes essential to overpower the stationary thermal plume, which disrupts this flow field. In areas with human presence, however, this technique is found to be particularly efficient since mobile heat sources do not generate a fixed thermal plume. A 0.05 m/s downward uniform flow field can settle 90% of particles within just 22 s. This flow pattern contributes to the swift settling of aerosol particles and effectively diminishes their dispersion. Employing this flow pattern in public places with increased foot traffic, like supermarkets, can lower the risk of contracting novel coronavirus without augmenting energy consumption. In order to implement the flow field in a part of the domain, a new air purification device is proposed in this study. The device combined with shelves can optimize the flow field uniformity through the MLA (PSO-SVR) algorithm and alteration of the air distribution structure. The uniformity of the final flow field increased to 0.925. The combination of data-driven MLA with CFD showed good performance in predicting the flow field uniformity. These findings offer valuable insights and practical applications for the prevention and control of respiratory diseases, particularly in post-epidemic scenarios.

Cleaning technologies integrated in duct flows for the inactivation of pathogenic microorganisms in indoor environments: A critical review of recent innovations and future challenges

Pathogenic microorganisms are a major concern in indoor environments, particularly in sensitive facilities such as hospitals, due to their potential to cause nosocomial infections. This study evaluates the concentration of airborne bacteria and fungi in the University Hospital Complex of Albacete (Spain), comparing the results with recent literature. Staphylococcus is identified as the most prevalent bacterial genus with a percentage distribution of 35%, while Aspergillus represents the dominant fungal genus at 34%. The lack of high Technology Readiness Levels (TRL 6, TRL 7) for effective indoor air purification requires research efforts to bridge this knowledge gap. A screening of disinfection technologies for pathogenic airborne microorganisms such as bacteria and fungi is conducted. The integration of filtration, irradiation or and (electro)chemical gas treatment systems in duct flows is discussed to enhance the design of the air-conditioning systems for indoor air purification. Concerns over microbial growth have led to recent studies on coating commercial fibrous air filters with antimicrobial particles (silver nanoparticles, iron oxide nanowires) and polymeric materials (polyaniline, polyvinylidene fluoride). Promising alternatives to traditional short-wave UV-C energy for disinfection include LED and Far-UVC irradiation systems. Additionally, research explores the use of TiO2 and TiO2 doped with metals (Ag, Cu, Pt) in filters with photocatalytic properties, enabling the utilization of visible or solar light. Hybrid photocatalysis, combining TiO2 with polymers, carbon nanomaterials, or MXene nanomaterials, enhances the photocatalytic process. Chemical treatment systems such as aerosolization of biocidal agents (benzalkonium chloride, hydrogen peroxide, chlorine dioxide or ozone) with their possible combination with other technologies such as adsorption, filtration or photocatalysis, are also tested for gas disinfection. However, the limited number of studies on the use of electrochemical technology poses a challenge for further investigation into gas-phase oxidant generation, without the formation of harmful by-products, to raise its TRL for effectively inactivating airborne microorganisms in indoor environments.

Airborne influenza virus shedding by patients in health care units: Removal mechanisms affecting virus transmission

In this study, we characterize the distribution of airborne viruses (influenza A/B) in hospital rooms of patients with confirmed infections. Concurrently, we monitored fine particulate matter (PM2.5 & PM10) and several physical parameters including the room air exchange rate, temperature, and relative humidity to identify corresponding correlations with virus transport and removal determinants. The results continue to raise concerns about indoor air quality (IAQ) in healthcare facilities and the potential exposure of patients, staff and visitors to aerosolized viruses as well as elevated indoor PM levels caused by outdoor sources and/or re-suspension of settled particles by indoor activities. The influenza A virus was detected in 42% of 33 monitored rooms, with viruses detectible up to 1.5 m away from the infected patient. Active coughing was a statistically significant variable that contributed to a higher positive rate of virus detection in the collected air samples. Viral load across patient rooms ranged between 222 and 5,760 copies/m3, with a mean of 820 copies/m3. Measured PM2.5 and PM10 levels exceeded IAQ daily exposure guidelines in most monitored rooms. Statistical and numerical analyses showed that dispersion was the dominant viral removal pathway followed by settling. Changes in the relative humidity and the room's temperature were had a significant impact on the viral load removal. In closure, we highlight the need for an integrated approach to control determinants of IAQ in patients' rooms.

Generative design for COVID-19 and future pathogens using stochastic multi-agent simulation

We propose a generative design workflow that integrates a stochastic multi-agent simulation with the intent of helping building designers reduce the risk posed by COVID-19 and future pathogens. Our custom simulation randomly generates activities and movements of individual occupants, tracking the amount of virus transmitted through air and surfaces from contagious to susceptible agents. The stochastic nature of the simulation requires that many repetitions be performed to achieve statistically reliable results. Accordingly, a series of initial experiments identified parameter values that balanced the trade-off between computational cost and accuracy. Applying generative design to a case study based on an existing office space reduced the predicted transmission by around 10% to 20% compared with a baseline set of layouts. Additionally, a qualitative examination of the generated layouts revealed design patterns that may reduce transmission. Stochastic multi-agent simulation is a computationally expensive yet plausible way to generate safer building designs.

Characterizing infection risk in a restaurant environment due to airborne diseases using discrete droplet dispersion simulations

The use of masks as a measure to control the spread of respiratory viruses has been widely acknowledged. However, there are instances where wearing a mask is not possible, making these environments potential vectors for virus transmission. Such environments can contain multiple sources of infection and are challenging to characterize in terms of infection risk. To address this issue, we have developed a methodology to investigate the role of ventilation in reducing the infection risk in such environments. We use a restaurant setting as a representative scenario to demonstrate the methodology. Using implicit large eddy simulations along with discrete droplet dispersion modeling we investigate the impact of ventilation and physical distance on the spread of respiratory viruses and the risk of infection. Our findings show that operating ventilation systems, such as mechanical mixing and increasing physical distance between subjects, can significantly reduce the average room infection risk and number of newly infected subjects. However, this observation is subject to the transmissibility of the airborne viruses. In the case of a highly transmissible virus, the use of mechanical mixing may be inconsequential when compared to only fresh air ventilation. These findings provide valuable insights into the mitigation of infection risk in situations where the use of masks is not possible.

Crowding on public transport using smart card data during the COVID-19 pandemic: New methodology and case study in Chile

Most crowding measures in public transportation are usually aggregated at a service level. This type of aggregation does not help to analyze microscopic behavior such as exposure risk to viruses. To bridge such a gap, our paper proposes four novel crowding measures that might be well suited to proxy virus exposure risk at public transport. In addition, we conduct a case study in Santiago, Chile, using smart card data of the buses system to compute the proposed measures for three different and relevant periods of the COVID-19 pandemic: before, during, and after Santiago's lockdown. We find that the governmental policies diminished public transport crowding considerably for the lockdown phase. The average exposure time when social distancing is not possible passes from 6.39 min before lockdown to 0.03 min during the lockdown, while the average number of encountered persons passes from 43.33 to 5.89. We shed light on how the pandemic impacts differ across various population groups in society. Our findings suggest that poorer municipalities returned faster to crowding levels similar to those before the pandemic.

Are We Truly Safe? Unfolding the Final Chapters of COVID-19 Walk-Through Booths

This research proposes a safety strategy for coronavirus disease 2019 (COVID-19) walk-through booths to optimize pandemic preparedness. These booths, designed for respiratory sample collection during the COVID-19 pandemic, effectively reduce infection risk and personal protective equipment-related fatigue among healthcare workers. However, inadequate disinfection and glove management could escalate infection transmission. Using computational fluid dynamics simulations, we analyzed droplet dispersion on booth surfaces and gloves under various wind conditions. Our findings suggest that when setting up COVID-19 walk-through booths, their location should be strategically chosen to minimize the effects of wind. All surfaces of booth gloves must be thoroughly disinfected with a certified disinfectant after nasopharyngeal swab collection. It is also recommended to wear disposable gloves over booth gloves when changing between patient examinations. In wind-affected areas, individuals nearby should not solely rely on the 2-meter distancing rule due to potential droplet spread from walk-through booths. We strongly recommend consistent and proper mask use for effective droplet blocking. Adherence to these guidelines can significantly enhance the safety and efficiency of walk-through booths, particularly in potential future pandemics.

From Microscopic Droplets to Macroscopic Crowds: Crossing the Scales in Models of Short-Range Respiratory Disease Transmission, with Application to COVID-19

Short-range exposure to airborne virus-laden respiratory droplets is an effective transmission route of respiratory diseases, as exemplified by Coronavirus Disease 2019 (COVID-19). In order to assess the risks associated with this pathway in daily-life settings involving tens to hundreds of individuals, the chasm needs to be bridged between fluid dynamical simulations and population-scale epidemiological models. This is achieved by simulating droplet trajectories at the microscale in numerous ambient flows, coarse-graining their results into spatio-temporal maps of viral concentration around the emitter, and coupling these maps to field-data about pedestrian crowds in different scenarios (streets, train stations, markets, queues, and street cafés). At the individual scale, the results highlight the paramount importance of the velocity of the ambient air flow relative to the emitter's motion. This aerodynamic effect, which disperses infectious aerosols, prevails over all other environmental variables. At the crowd's scale, the method yields a ranking of the scenarios by the risks of new infections, dominated by the street cafés and then the outdoor market. While the effect of light winds on the qualitative ranking is fairly marginal, even the most modest air flows dramatically lower the quantitative rates of new infections.

Determining the filtration effectiveness of non-standard respiratory protective devices by an ad-hoc laboratory methodology

The recent pandemic caused by COVID-19 profoundly changed people's habits. Wearing a face mask has become usual in everyday life to reduce the risk of infection from airborne diseases. At the beginning of the pandemic, the massive request of surgical or filtering face piece (FFP) masks resulted in a global shortage of these devices for the most exposed people, such as healthcare workers. Due to this high demand for respiratory protective devices, many industrial plants have partly converted to the production of face masks using adapted materials and not complying with any specific regulation (non-standard respiratory protective devices or community masks). In this work, an ad-hoc laboratory methodology has been developed to evaluate the filtration efficiency of the materials that compose the community masks using specific instrumentation. The instrumentation consists of three main tools: an aerosol generator, a specifically designed measuring chamber, and an optical particle sizer (OPS) for the measurement of aerosol concentration. The generated aerosol was sent into the measuring chamber, divided into two separate sections by the respiratory mask. The OPS measured the aerosol mass concentration upstream and downstream of the respiratory mask, and from the concentration difference the filtration efficiency was evaluated. The proposed methodology has been validated by evaluating the particle filtration efficiency (PFE) of certified respiratory masks and was then applied for the evaluation of the filtration efficiency of different types of non-standard or community masks to analyze their effectiveness in protecting from the risk of infection of airborne diseases.

Fates of Emitted Particles Depending on Mask Wearing Using an Approach Validated Across Spatial Scales

The spread of emitted potentially virus-laden aerosol particles is known to be highly dependent on whether a mask is worn by an infected person and on the emission scenario, i.e., whether the person is coughing, speaking, or breathing. The aim of this work is to investigate in detail the fates of particles emitted by a person wearing a perfectly fitting, a naturally fitted mask with leakage, and no mask depending on the emission scenario. Therefore, a two-scale numerical workflow is proposed where parameters are carried through from a micro-scale where the fibers of the mask filter medium and the aerosol particles are resolved to a macro-scale and validated by comparison to experimental measurements of fractional filtration efficiency and pressure drop of the filter medium as well as pressure drop of the mask. It turns out that masks reduce the number of both emitted and inhaled particles significantly even with leakage. While without a mask, the person opposite of an infected person is generally at the highest risk of being infected, a mask worn by an infected person speaking or coughing will deflect the flow leading to the fact that the person behind the infected person might inhale the largest number of aerosol particles.

Aerosol generation during coughing: an observational study

OBJECTIVE

Coronavirus disease 2019 has highlighted the lack of knowledge on aerosol exposure during respiratory activity and aerosol-generating procedures. This study sought to determine the aerosol concentrations generated by coughing to better understand, and to set a standard for studying, aerosols generated in medical procedures.

METHODS

Aerosol exposure during coughing was measured in 37 healthy volunteers in the operating theatre with an optical particle sizer, from 40 cm, 70 cm and 100 cm distances.

RESULTS

Altogether, 306 volitional and 15 involuntary coughs were measured. No differences between groups were observed.

CONCLUSION

Many medical procedures are expected to generate aerosols; it is unclear whether they are higher risk than normal respiratory activity. The measured aerosol exposure can be used to determine the risk for significant aerosol generation during medical procedures. Considerable variation of aerosol generation during cough was observed between individuals, but whether cough was volitional or involuntary made no difference to aerosol production.

Prediction of COVID-19 Infection in Dental Clinic by CFD and Wells-Riley Model, Identifying Safe Area and Proper Ventilation Velocity: Prédiction de l'infection au COVID-19 dans une clinique dentaire par CFD et modèle Wells-Riley, identification de la zone de sécurité et de la vitesse de ventilation appropriée

The COVID-19 virus is recognized worldwide as a significant public health threat. A dental clinic is one of the most dangerous places in the COVID-19 epidemic, and disease transmission is rapid. Planning is essential to create the right conditions in the dental clinic. In this study, the cough of an infected person is examined in a 9 × 6 × 3 m³ area. Computational fluid dynamic (CFD) is applied to simulate the flow field and to determine the dispersion path. The innovation of this research is checking the risk of infection for each person in the designated dental clinic, choosing the suitable velocity for ventilation, and identifying safe areas. In the first step, the effects of different ventilation velocities on the dispersion of virus-infected droplets are investigated, and the most appropriate ventilation flow velocity has been identified. Then, the results of the presence or absence of a dental clinic separator shield on the spread of respiratory droplets have been identified. Finally, the risk of infection (by the Wells-Riley equation) is assessed, and safe areas are identified. The effect of RH on droplet evaporation in this dental clinic is assumed to be 50%. The N_Tn values in an area with a separator shield are less than 1%. When there is a separator shield, the infection risk of people in A3 and A7 (the other side of the separator shield) is reduced from 23% to 4%, and 21% to 2%, respectively.

Mechanisms controlling the transport and evaporation of human exhaled respiratory droplets containing the severe acute respiratory syndrome coronavirus: a review

Transmission of the coronavirus disease 2019 is still ongoing despite mass vaccination, lockdowns, and other drastic measures to control the pandemic. This is due partly to our lack of understanding on the multiphase flow mechanics that control droplet transport and viral transmission dynamics. Various models of droplet evaporation have been reported, yet there is still limited knowledge about the influence of physicochemical parameters on the transport of respiratory droplets carrying the severe acute respiratory syndrome coronavirus 2. Here we review the effects of initial droplet size, environmental conditions, virus mutation, and non-volatile components on droplet evaporation and dispersion, and on virus stability. We present experimental and computational methods to analyze droplet transport, and factors controlling transport and evaporation. Methods include thermal manikins, flow techniques, aerosol-generating techniques, nucleic acid-based assays, antibody-based assays, polymerase chain reaction, loop-mediated isothermal amplification, field-effect transistor-based assay, and discrete and gas-phase modeling. Controlling factors include environmental conditions, turbulence, ventilation, ambient temperature, relative humidity, droplet size distribution, non-volatile components, evaporation and mutation. Current results show that medium-sized droplets, e.g., 50 µm, are sensitive to relative humidity. Medium-sized droplets experience delayed evaporation at high relative humidity, and increase airborne lifetime and travel distance. By contrast, at low relative humidity, medium-sized droplets quickly shrink to droplet nuclei and follow the cough jet. Virus inactivation within a few hours generally occurs at temperatures above 40 °C, and the presence of viral particles in aerosols impedes droplet evaporation.

The impact of mass gatherings on the local transmission of COVID-19 and the implications for social distancing policies: Evidence from Hong Kong

Mass gatherings provide conditions for the transmission of infectious diseases and pose complex challenges to public health. Faced with the COVID-19 pandemic, governments and health experts called for suspension of gatherings in order to reduce social contact via which virus is transmitted. However, few studies have investigated the contribution of mass gatherings to COVID-19 transmission in local communities. In Hong Kong, the coincidence of the relaxation of group gathering restrictions with demonstrations against the National Security Law in mid-2020 raised concerns about the safety of mass gatherings under the pandemic. Therefore, this study examines the impacts of mass gatherings on the local transmission of COVID-19 and evaluates the importance of social distancing policies. With an aggregated dataset of epidemiological, city-level meteorological and socioeconomic data, a Synthetic Control Method (SCM) is used for constructing a 'synthetic Hong Kong' from over 200 Chinese cities. This counterfactual control unit is used to simulate COVID-19 infection patterns (i.e., the number of total cases and daily new cases) in the absence of mass gatherings. Comparing the hypothetical trends and the actual ones, our results indicate that the infection rate observed in Hong Kong is substantially higher than that in the counterfactual control unit (2.63% vs. 0.07%). As estimated, mass gatherings increased the number of new infections by 62 cases (or 87.58% of total new cases) over the 10-day period and by 737 cases (or 97.23%) over the 30-day period. These findings suggest the necessity of tightening social distancing policies, especially the prohibition on group gathering regulation (POGGR), to prevent and control COVID-19 outbreaks.

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.

Is safe distance enough to prevent COVID-19? Dispersion and tracking of aerosols in various artificial ventilation conditions using OpenFOAM

The current COVID-19 pandemic has underlined the importance of learning more about aerosols and particles that migrate through the airways when a person sneezes, coughs and speaks. The coronavirus transmission is influenced by particle movement, which contributes to the emergence of regulations on social distance, use of masks and face shield, crowded assemblies, and daily social activity in domestic, public, and corporate areas. Understanding the transmission of aerosols under different micro-environmental conditions, closed, or ventilated, has become extremely important to regulate safe social distances. The present work attempts to simulate the airborne transmission of coronavirus-laden particles under different respiratory-related activities, i.e., coughing and speaking, using CFD modelling through OpenFOAM v8. The dispersion coupled with the Discrete Phase Method (DPM) has been simulated to develop a better understanding of virus carrier particles transmission processes and their path trailing under different ventilation scenarios. The preliminary results of this study with respect to flow fields were in close agreement with published literature, which was then extended under varied ventilation scenarios and respiratory-related activities. The study observed that improper wearing of mask leads to escape of SARS-CoV-2 containminated aerosols having a smaller aerodynamic diameter from the gap between face mask and face, infecting different surfaces in the vicinity. It was also observed that aerosol propagation infecting the area through coughing is a faster phenomenon compared to the propagation of coronavirus-laden particles during speaking. The study's findings will help decision-makers formulate common but differentiated guidelines for safe distancing under different micro-environmental conditions.

A computational framework for transmission risk assessment of aerosolized particles in classrooms

Infectious airborne diseases like the recent COVID-19 pandemic render confined spaces high-risk areas. However, in-person activities like teaching in classroom settings and government services are often expected to continue or restart quickly. It becomes important to evaluate the risk of airborne disease transmission while accounting for the physical presence of humans, furniture, and electronic equipment, as well as ventilation. Here, we present a computational framework and study based on detailed flow physics simulations that allow straightforward evaluation of various seating and operating scenarios to identify risk factors and assess the effectiveness of various mitigation strategies. These scenarios include seating arrangement changes, presence/absence of computer screens, ventilation rate changes, and presence/absence of mask-wearing. This approach democratizes risk assessment by automating a key bottleneck in simulation-based analysis-creating an adequately refined mesh around multiple complex geometries. Not surprisingly, we find that wearing masks (with at least 74% inward protection efficiency) significantly reduced transmission risk against unmasked and infected individuals. While the use of face masks is known to reduce the risk of transmission, we perform a systematic computational study of the transmission risk due to variations in room occupancy, seating layout and air change rates. In addition, our findings on the efficacy of face masks further support use of face masks. The availability of such an analysis approach will allow education administrators, government officials (courthouses, police stations), and hospital administrators to make informed decisions on seating arrangements and operating procedures.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00366-022-01773-9.

Environmental Dissemination of SARS-CoV-2 in a University Hospital during the COVID-19 5th Wave Delta Variant Peak in Castile-León, Spain

The dominant SARS-CoV-2 Delta variant (B.1.617.2) became the main circulating variant among countries by mid 2021. Attention was raised to the increased risk of airborne transmission, leading to nosocomial outbreaks even among vaccinated individuals. Considering the increased number of COVID-19 hospital admissions fueled by the spread of the variant, with Spain showing the highest COVID-19 rates in mainland Europe by July 2021, the aim of this study was to assess SARS-CoV-2 environmental contamination in different areas of a University Hospital in the region of Castile-León, Spain, during the peak of the 5th wave of COVID-19 in the country (July 2021). Air samples were collected from sixteen different areas of the Hospital using a Coriolis® μ air sampler. Surface samples were collected in these same areas using sterile flocked plastic swabs. RNA extraction followed by a one-step RT-qPCR were performed for detection of SARS-CoV-2 RNA. Of the 21 air samples, only one was positive for SARS-CoV-2 RNA, from the emergency waiting room. Of the 40 surface samples, 2 were positive for SARS-CoV-2 RNA, both from the microbiology laboratory. These results may be relevant for risk assessment of nosocomial infection within healthcare facilities, thus helping prevent and minimize healthcare staff's exposure to SARS-CoV-2, reinforcing the importance of always wearing appropriate and well-fit masks at all times and proper PPE when in contact with infected patients.

A Numerical Investigation into the Spread Characteristics of a Human Virus-Carrying Droplet in a Classroom Environment

In public health, the transmission characteristics and laws of highly infectious virus-carrying particles in the air environment have become a hot topic. The study on the spread characteristics of human virus-carrying droplets in a typical densely populated space is necessary. As such, a classroom space lattice Boltzmann method (LBM) model with a dense population is established to simulate and analyze the spreading and diffusing behavior of pathogenic droplets. The results show that the dispersion density is mainly affected by the mainstream wind direction in the area of concern, and particle aggregation is more likely to form in the area close to the wind disturbance. Due to the dense thermal plumes, the droplet movement is a clear convergence towards the upper space of the classroom. This could explain the fact that people living above confirmed cases are now more likely to be infected.

Novel aerosol detection platform for SARS‑CoV‑2: Based on specific magnetic nanoparticles adsorption sampling and digital droplet PCR detection

The SARS‑CoV‑2 virus is released from an infectious source (such as a sick person) and adsorbed on aerosols, which can form pathogenic microorganism aerosols, which can affect human health through airborne transmission. Efficient sampling and accurate detection of microorganisms in aerosols are the premise and basis for studying their properties and evaluating their hazard. In this study, we built a set of sub-micron aerosol detection platform, and carried out a simulation experiment on the SARS‑CoV‑2 aerosol in the air by wet-wall cyclone combined with immunomagnetic nanoparticle adsorption sampling and ddPCR. The feasibility of the system in aerosol detection was verified, and the influencing factors in the detection process were experimentally tested. As a result, the sampling efficiency was 29.77%, and extraction efficiency was 98.57%. The minimum detection limit per unit volume of aerosols was 250 copies (102 copies/mL, concentration factor 2.5).

Reducing Vaccinia virus transmission indoors within 60 seconds: Applying SAFEAIR-X aerosol with Iodine-V as a disinfectant

Iodine-V ((C26H39N4O15)x * (I2)y) demonstrates an in vitro virucidal activity by deactivating SARS-CoV-2 viral titers. It combines elemental iodine (I2) and fulvic acid (C14H12O8), forming a clathrate compound. The antiviral properties of Iodine-V reduce viral load in the air to inhibit viral transmission indoors. This antiviral property was applied to form a disinfectant solution called SAFEAIR-X Aerosol. The current study evaluates the antiviral efficacy of Iodine-V in aerosol form in a prototype called SAFEAIR-X Aerosol. The experiment measured the antiviral efficacy of SAFEAIR-X following exposure to the Vaccinia virus (VACV) samples as a confirmed surrogate for SARS-CoV-2. The SAFEAIR-X showed 96% effectiveness, with 2 seconds of spraying duration and 60 seconds of contact time releasing less than 0.0001 ppm of iodine into the air, and a log reduction value of 1.50 at 60 seconds in 2 out of 3 tests was observed. Therefore, this study demonstrates SAFEAIR-X aerosol as a potential indoor surface and air disinfectant.

How do temperature, humidity, and air saturation state affect the COVID-19 transmission risk?

Environmental parameters have a significant impact on the spread of respiratory viral diseases (temperature (T), relative humidity (RH), and air saturation state). T and RH are strongly correlated with viral inactivation in the air, whereas supersaturated air can promote droplet deposition in the respiratory tract. This study introduces a new concept, the dynamic virus deposition ratio (α), that reflects the dynamic changes in viral inactivation and droplet deposition under varying ambient environments. A non-steady-state-modified Wells-Riley model is established to predict the infection risk of shared air space and highlight the high-risk environmental conditions. Findings reveal that a rise in T would significantly reduce the transmission of COVID-19 in the cold season, while the effect is not significant in the hot season. The infection risk under low-T and high-RH conditions, such as the frozen seafood market, is substantially underestimated, which should be taken seriously. The study encourages selected containment measures against high-risk environmental conditions and cross-discipline management in the public health crisis based on meteorology, government, and medical research.

Virus transmission risk of college students in railway station during Post-COVID-19 era: Combining the social force model and the virus transmission model

In the post-epidemic era, people's lives are gradually returning to normal, and travel is gradually resuming. The safe evacuation of cross-regional travelers in railway station has also attracted more and more attention, especially the evacuation behavior of college students in railway station. In this paper, considering the pedestrian dynamics mechanism in the emergency evacuation process during the COVID-19 normalized epidemic prevention and control, an Agent-based social force model was established to simulate the activities of college students in railway station. Combined with the virus infection transmission model, Monte Carlo simulation was used to calculate the total exposure time and the number of high-risk exposed people in the railway station evacuation process. In addition, sensitivity analysis was conducted on the total exposure time and the number of high-risk exposed people under 180 combinations of the number of initial infections, social distance, and the proportion of people wearing masks incorrectly. The results show that with the increase of social distances, the total exposure time and the number of high-risk exposures do not always decrease, but increase in some cases. The presence or absence of obstacles in the evacuation scene has no significant difference in the effects on total exposure time and the number of high-risk exposures. During the evacuation behavior of college students in railway station, choosing the appropriate number of lines can effectively reduce the total exposure time and the number of high-risk exposures. Finally, some policy suggestions are proposed to reduce the risk of virus transmission in the railway station evacuation process, such as choosing dynamic and reasonable social distance and the number of queues, and reducing obstacles.

A frontal air intake may improve the natural ventilation in urban buses

In this report we analyze the air flow across the open windows (natural ventilation) of an urban bus model and the consequent dispersion of aerosols emitted in the passengers area. The methods include computational fluid dynamics simulations and three ways to characterize the dispersion of passive tracers: a continuous concentration-based model, a discrete random model and a parametric scalar based on the so-called mean age of air. We also conducted experiments using a 1:10 scale bus model and [Formula: see text] as a passive tracer to assess the ventilation characteristics. We found that dispersion and expulsion of aerosols is driven by a negative pressure in the standard bus design equipped with lateral windows. Also, the average age of air is 6 minutes while the air flow promotes aerosol accumulation to the front (driver's area). To speed up the expulsion of aerosols and reduce their in-cabin accumulation, we propose a bus bodywork prototype having a frontal air intake. All the numerical models and experiments conducted in this work agreed that the expulsion of aerosols in this novel configuration is significantly increased while the average age of air is reduced to 50 seconds. The average air flow also changes with the presence of frontal air intakes and, as a consequence, the expulsion of aerosols is now driven by a frontal velocity field.

Airborne transmission of biological agents within the indoor built environment: a multidisciplinary review

The nature and airborne dispersion of the underestimated biological agents, monitoring, analysis and transmission among the human occupants into building environment is a major challenge of today. Those agents play a crucial role in ensuring comfortable, healthy and risk-free conditions into indoor working and leaving spaces. It is known that ventilation systems influence strongly the transmission of indoor air pollutants, with scarce information although to have been reported for biological agents until 2019. The biological agents' source release and the trajectory of airborne transmission are both important in terms of optimising the design of the heating, ventilation and air conditioning systems of the future. In addition, modelling via computational fluid dynamics (CFD) will become a more valuable tool in foreseeing risks and tackle hazards when pollutants and biological agents released into closed spaces. Promising results on the prediction of their dispersion routes and concentration levels, as well as the selection of the appropriate ventilation strategy, provide crucial information on risk minimisation of the airborne transmission among humans. Under this context, the present multidisciplinary review considers four interrelated aspects of the dispersion of biological agents in closed spaces, (a) the nature and airborne transmission route of the examined agents, (b) the biological origin and health effects of the major microbial pathogens on the human respiratory system, (c) the role of heating, ventilation and air-conditioning systems in the airborne transmission and (d) the associated computer modelling approaches. This adopted methodology allows the discussion of the existing findings, on-going research, identification of the main research gaps and future directions from a multidisciplinary point of view which will be helpful for substantial innovations in the field.

Infectiousness of places - Impact of multiscale human activity places in the transmission of COVID-19

COVID-19 raises attention to epidemic transmission in various places. This study analyzes the transmission risks associated with human activity places at multiple scales, including different types of settlements and eleven types of specific establishments (restaurants, bars, etc.), using COVID-19 data in 906 urban areas across four continents. Through a difference-in-difference approach, we identify the causal effects of activities at various places on epidemic transmission. We find that at the micro-scale, though the transmission risks at different establishments differ across countries, sports, entertainment, and catering establishments are generally more infectious. At the macro-scale, contradicting common beliefs, it is consistent across countries that transmission does not increase with settlement size and density. It is also consistent that specific establishments play a lesser role in transmission in larger settlements, suggesting more transmission happening elsewhere. These findings contribute to building a system of knowledge on the linkage between places, human activities, and disease transmission.

Combining Phi6 as a surrogate virus and computational large-eddy simulations to study airborne transmission of SARS-CoV-2 in a restaurant

COVID-19 has highlighted the need for indoor risk-reduction strategies. Our aim is to provide information about the virus dispersion and attempts to reduce the infection risk. Indoor transmission was studied simulating a dining situation in a restaurant. Aerosolized Phi6 viruses were detected with several methods. The aerosol dispersion was modeled by using the Large-Eddy Simulation (LES) technique. Three risk-reduction strategies were studied: (1) augmenting ventilation with air purifiers, (2) spatial partitioning with dividers, and (3) combination of 1 and 2. In all simulations infectious viruses were detected throughout the space proving the existence long-distance aerosol transmission indoors. Experimental cumulative virus numbers and LES dispersion results were qualitatively similar. The LES results were further utilized to derive the evolution of infection probability. Air purifiers augmenting the effective ventilation rate by 65% reduced the spatially averaged infection probability by 30%-32%. This relative reduction manifests with approximately 15 min lag as aerosol dispersion only gradually reaches the purifier units. Both viral findings and LES results confirm that spatial partitioning has a negligible effect on the mean infection-probability indoors, but may affect the local levels adversely. Exploitation of high-resolution LES jointly with microbiological measurements enables an informative interpretation of the experimental results and facilitates a more complete risk assessment.

Microstructural evaluation and recommendations for face masks in community use to reduce the transmission of respiratory infectious diseases

BACKGROUND AND OBJECTIVE

Recommendations for the use of face masks to prevent and protect against the aerosols (≤5µm) and respiratory droplet particles (≥5µm), which can carry and transmit respiratory infections including severe acute respiratory syndrome coronavirus (SARS-CoV-2), have been in effect since the early stages of the coronavirus disease 2019 (COVID-19). The particle filtration efficiency (PFE) and air permeability are the most crucial factors affecting the level of pathogen transmission and breathability, i.e. wearer comfort, which should be investigated in detail.

METHODS

In this context, this article presents a novel assessment framework for face masks combining X-ray microtomography and computational fluid dynamics simulations. In consideration to their widespread public use, two types of face masks were assessed: (I) two layer non-woven face masks and (II) the surgical masks (made out of a melt-blown fabric layer covered with two non-woven fabric layers).

RESULTS

The results demonstrate that the surgical masks provide PFEs over 75% for particles with diameter over 0.1µm while two layer face masks are found out to have insufficient PFEs, even for the particles with diameter over 2µm (corresponding PFE is computed as 47.2%). Thus, existence of both the non-woven fabric layers for mechanical filtration and insertion of melt-blown fabric layer(s) for electrostatic filtration in the face masks were found to be highly critical to prevent the airborne pathogen transmission.

CONCLUSIONS

The present framework would assist in computational assessment of commonly used face mask types based on their microstructural characteristics including fiber diameter, orientation distributions and fiber network density. Therefore, it would be also possible to provide new yet feasible design routes for face masks to ensure reliable personal protection and optimal breathability.

Risk assessment for long- and short-range airborne transmission of SARS-CoV-2, indoors and outdoors

Preventive measures to reduce infection are needed to combat the COVID-19 pandemic and prepare for a possible endemic phase. Current prophylactic vaccines are highly effective to prevent disease but lose their ability to reduce viral transmission as viral evolution leads to increasing immune escape. Long-term proactive public health policies must therefore complement vaccination with available nonpharmaceutical interventions aiming to reduce the viral transmission risk in public spaces. Here, we revisit the quantitative assessment of airborne transmission risk, considering asymptotic limits that considerably simplify its expression. We show that the aerosol transmission risk is the product of three factors: a biological factor that depends on the viral strain, a hydrodynamical factor defined as the ratio of concentration in viral particles between inhaled and exhaled air, and a face mask filtering factor. The short-range contribution to the risk, present both indoors and outdoors, is related to the turbulent dispersion of exhaled aerosols by air drafts and by convection (indoors), or by the wind (outdoors). We show experimentally that airborne droplets and CO2 molecules present the same dispersion. As a consequence, the dilution factor, and therefore the risk, can be measured quantitatively using the CO2 concentration, regardless of the room volume, the flow rate of fresh air, and the occupancy. We show that the dispersion cone leads to a concentration in viral particles, and therefore a short-range transmission risk, inversely proportional to the squared distance to an infected person and to the flow velocity. The aerosolization criterion derived as an intermediate result, which compares the Stokes relaxation time to the Lagrangian time-scale, may find application for a broad class of aerosol-borne pathogens and pollutants.

Pandemic management requires exposure science

COVID-19 was first detected in Wuhan, China, on 8.12.2019, and WHO announced it a pandemic on 11.3.2020. No vaccines or medical cures against COVID-19 were available in the first corona year. Instead, different combinations of generic non-pharmaceutical interventions - to slow down the spread of infections via exposure restrictions to 'flatten the curve' so that it would not overburden the health care systems, or to suppress the virus to extinction - were applied with varying levels of strictness, duration and success in the Pacific and North Atlantic regions. Due to an old misconception, almost all public health authorities dismissed the possibility that the virus would be transmitted via air. Opportunities to reduce the inhalation exposure - such as wearing effective FFP2/N95 respirators, improving ventilation and indoor air cleaning - were missed, and instead, hands were washed and surfaces disinfected. The fact that aerosols were acknowledged as the main route of COVID-19 transmission in 2021 opened avenues for more efficient and socially less disruptive exposure and risk reduction policies that are discussed and evaluated here, demonstrating that indoor air and exposure sciences are crucial for successful management of pandemics. To effectively apply environmental and personal exposure mitigation measures, exposure science needs to target the human-to-human exposure pathways of the virus.

A mesoscale agent based modeling framework for flow-mediated infection transmission in indoor occupied spaces

The ongoing Covid-19 pandemic, and its associated public health and socioeconomic burden, has reaffirmed the necessity for a comprehensive understanding of flow-mediated infection transmission in occupied indoor spaces. This is an inherently multiscale problem, and suitable investigation approaches that can enable evidence-based decision-making for infection control strategies, interventions, and policies; will need to account for flow physics, and occupant behavior. Here, we present a mesoscale infection transmission model for human occupied indoor spaces, by integrating an agent-based human interaction model with a flow physics model for respiratory droplet dynamics and transport. We outline the mathematical and algorithmic details of the modeling framework, and demonstrate its validity using two simple simulation scenarios that verify each of the major sub-models. We then present a detailed case-study of infection transmission in a model indoor space with 60 human occupants; using a systematic set of simulations representing various flow scenarios. Data from the simulations illustrate the utility and efficacy of the devised mesoscale model in resolving flow-mediated infection transmission; and elucidate key trends in infection transmission dynamics amongst the human occupants.

Analytic modeling and risk assessment of aerial transmission of SARS-CoV-2 virus through vaping expirations in shared micro-environments

It is well known that airborne transmission of COVID-19 in indoor spaces occurs through various respiratory activities: breathing, vocalizing, coughing, and sneezing. However, there is a complete lack of knowledge of its possible transmission through exhalations of e-cigarette aerosol (ECA), which is also a respiratory activity. E-cigarettes have become widely popular among smokers seeking a much safer way of nicotine consumption than smoking. Due to restrictive lockdown measures taken during the COVID-19 pandemic, many smokers and vapers (e-cigarette users) were confined to shared indoor spaces, making it necessary to assess the risk of SARS-CoV-2 virus aerial transmission through their exhalations. We summarize inferred knowledge of respiratory particles emission and transport through ECA, as well as a theoretical framework for explaining the visibility of exhaled ECA, which has safety implications and is absent in other respiratory activities (apart from smoking). We also summarize and briefly discuss the effects of new SARS-CoV-2 variants, vaccination rates, and environmental factors that may influence the spread of COVID-19. To estimate the risk of SARS-CoV-2 virus aerial transmission associated with vaping exhalations, we adapt a theoretical risk model that has been used to analyze the risks associated with other respiratory activities in shared indoor spaces. We consider home and restaurant scenarios, with natural and mechanical ventilation, with occupants wearing and not wearing face masks. We consider as "control case" or baseline risk scenario an indoor space (home and restaurant) where respiratory droplets and droplet nuclei are uniformly distributed and aerial contagion risk might originate exclusively from occupants exclusively rest breathing, assuming this to be the only (unavoidable) respiratory activity they all carry on. If an infected occupant uses an e-cigarette in a home or restaurant scenarios, bystanders not wearing face masks exposed to the resulting ECA expirations face a [Formula: see text] increase of risk of contagion with respect the control case. This relative added risk with respect to the control case becomes [Formula: see text] for high-intensity vaping, [Formula: see text], and over [Formula: see text] for speaking for various periods or coughing (all without vaping). Infectious emissions are significantly modified by mechanical ventilation, face mask usage, vaccination, and environmental factors, but given the lack of empiric evidence, we assume as a working hypothesis that all basic parameters of respiratory activities are equally (or roughly equally) affected by these factors. Hence, the relative risk percentages with respect to the control state should remain roughly the same under a wide range of varying conditions. By avoiding direct exposure to the visible exhaled vaping jet, wearers of commonly used face masks are well protected from respiratory droplets and droplet nuclei directly emitted by mask-less vapers. Compared to the control case of an already existing (unavoidable) risk from continuous breathing, vaping emissions in shared indoor spaces pose just a negligible additional risk of COVID-19 contagion. We consider that it is not necessary to take additional preventive measures beyond those already prescribed (1.5 m separation and wearing face masks) in order to protect bystanders from this contagion.

Aerosol concentrations and size distributions during clinical dental procedures

Background

Suspected aerosol-generating dental instruments may cause risks for operators by transmitting pathogens, such as the SARS-CoV-2 virus. The aim of our study was to measure aerosol generation in various dental procedures in clinical settings.

Methods

The study population comprised of 84 patients who underwent 253 different dental procedures measured with Optical Particle Sizer in a dental office setting. Aerosol particles from 0.3 to 10 μm in diameter were measured. Dental procedures included oral examinations (N = 52), restorative procedures with air turbine handpiece (N = 8), high-speed (N = 6) and low-speed (N = 30) handpieces, ultrasonic scaling (N = 31), periodontal treatment using hand instruments (N = 60), endodontic treatment (N = 12), intraoral radiographs (N = 24), and dental local anesthesia (N = 31).

Results

Air turbine handpieces significantly elevated <1 μm particle median (p = 0.013) and maximum (p = 0.016) aerosol number concentrations as well as aerosol particle mass concentrations (p = 0.046 and p = 0.006) compared to the background aerosol levels preceding the operation. Low-speed dental handpieces elevated >5 μm median (p = 0.023), maximum (p = 0.013) particle number concentrations,> 5 μm particle mass concentrations (p = 0.021) and maximum total particle mass concentrations (p = 0.022). High-speed dental handpieces elevated aerosol concentration levels compared to the levels produced during oral examination.

Conclusions

Air turbine handpieces produced the highest levels of <1 μm aerosols and total particle number concentrations when compared to the other commonly used instruments. In addition, high- and low-speed dental handpieces and ultrasonic scalers elevated the aerosol concentration levels compared to the aerosol levels measured during oral examination. These aerosol-generating procedures, involving air turbine, high- and low-speed handpiece, and ultrasonic scaler, should be performed with caution.

Clinical significance

Aerosol generating dental instruments, especially air turbine, should be used with adequate precautions (rubber dam, high-volume evacuation, FFP-respirators), because aerosols can cause a potential risk for operators and substitution of air turbine for high-speed dental handpiece in poor epidemic situations should be considered to reduce the risk of aerosol transmission.

Impacts of human movement and ventilation mode on the indoor environment, droplet evaporation, and aerosol transmission risk at airport terminals

The dispersion of the coronavirus pandemic has caused immense damage worldwide, and people have begun to ruminate epidemic prevention strategies for public places. Airport terminals with a high number of occupied passengers have become potentially high-risk regions for aerosol transmission of coronavirus disease 2019 (COVID-19). In this study, the Eulerian-Lagrangian approach and realizable k-ε turbulence model were used to numerically simulate airflow organization and aerosol transmission when passengers are moving slowly in a line. During the aerosol transmission period, evaporation was considered a key factor influencing the particle size distribution at the beginning of aerosol transmission from humans. Moreover, passenger movement at the airport terminal was attained by employing dynamic mesh algorithms. Based on the relative direction of passengers and air vents when queuing in the terminal building, we studied three conditions: windward walking, leeward walking, and crosswind walking. The results of this study showed that the walking has an important influence on droplet distribution. Droplet distribution indicates that individuals standing behind patients during queuing movements have a higher risk of infection than those standing in front of them. A significant aerosol accumulation was discovered at 0.5 m behind the patient when passengers moved simultaneously. An aerosol transmission distance of 15 s aligned with the passenger's walking direction could reach up to 9.32 m. Furthermore, although the evaporation time of the large droplets was longer than that of the small droplets, both large and small droplets evaporated rapidly after exhalation. The crosswind influence caused the droplets to travel farther away in a direction perpendicular to human movement, which increased the distance by approximately 1.26 m compared to the absence of the crosswind influence.

SARS-CoV-2 indoor environment contamination with epidemiological and experimental investigations

SARS-CoV-2 has been detected both in air and on surfaces, but questions remain about the patient-specific and environmental factors affecting virus transmission. Additionally, more detailed information on viral sampling of the air is needed. This prospective cohort study (N = 56) presents results from 258 air and 252 surface samples from the surroundings of 23 hospitalized and eight home-treated COVID-19 index patients between July 2020 and March 2021 and compares the results between the measured environments and patient factors. Additionally, epidemiological and experimental investigations were performed. The proportions of qRT-PCR-positive air (10.7% hospital/17.6% homes) and surface samples (8.8%/12.9%) showed statistical similarity in hospital and homes. Significant SARS-CoV-2 air contamination was observed in a large (655.25 m³ ) mechanically ventilated (1.67 air changes per hour, 32.4-421 L/s/patient) patient hall even with only two patients present. All positive air samples were obtained in the absence of aerosol-generating procedures. In four cases, positive environmental samples were detected after the patients had developed a neutralizing IgG response. SARS-CoV-2 RNA was detected in the following particle sizes: 0.65-4.7 μm, 7.0-12.0 μm, >10 μm, and <100 μm. Appropriate infection control against airborne and surface transmission routes is needed in both environments, even after antibody production has begun.