Modelling uncertainty in the relative risk of exposure to the SARS-CoV-2 virus by airborne aerosol transmission in well mixed indoor air

On modelling airborne infection risk

Airborne infection risk analysis is usually performed for enclosed spaces where susceptible individuals are exposed to infectious airborne respiratory droplets by inhalation. It is usually based on exponential, dose-response models of which a widely used variant is the Wells-Riley (WR) model. We revisit this infection-risk estimate and extend it to the population level. We use an epidemiological model where the mode of pathogen transmission, airborne or contact, is explicitly considered. We illustrate the link between epidemiological models and the WR and the Gammaitoni and Nucci models. We argue that airborne infection quanta are, up to an overall density, airborne infectious respiratory droplets modified by a parameter that depends on biological properties of the pathogen, physical properties of the droplet and behavioural properties of the individual. We calculate the time-dependent risk of being infected for two scenarios. We show how the epidemic infection risk depends on the viral latent period and the event time, the time infection occurs. Infection risk follows the dynamics of the infected population. As the latent period decreases, infection risk increases. The longer a susceptible is present in the epidemic, the higher its risk of infection for equal exposure time to the pathogen is.

Architectural interventions to mitigate the spread of SARS-CoV-2 in emergency departments

INTRODUCTION

Emergency departments (EDs) are a critical entry gate for infectious agents into hospitals. In this interdisciplinary study, we explore how infection prevention and control (IPC) architectural interventions mitigate the spread of emerging respiratory pathogens using the example of SARS-CoV-2 in a prototypical ED.

METHODS

Using an agent-based approach, we integrated data on patients' and healthcare workers' (HCWs) routines and the architectural characteristics of key ED areas. We estimated the number of transmissions in the ED by modelling the interactions between and among patients and HCWs. Architectural interventions were guided towards the gradual separation of pathogen carriers, compliance with a minimum interpersonal distance, and deconcentrating airborne pathogens (higher air exchange rates (AERs)). Interventions were epidemiologically evaluated for their mitigation effects on diverse endpoints.

RESULTS

Simulation results indicated that higher AERs in the ED (compared with baseline) may provide a moderate level of infection mitigation (incidence rate ratio (IRR) of 0.95 (95% confidence interval (CI) 0.93-0.98)) while the overall burden decreased more when rooms in examination areas were separated (IRR of 0.78 (95% CI 0.76-0.81)) or when the size of the ED base was increased (IRR of 0.79 (95% CI 0.78-0.81)). The reduction in SARS-CoV-2-associated nosocomial transmissions was largest when architectural interventions were combined (IRR of 0.61 (95% CI 0.59-0.63)).

CONCLUSIONS

These modelling results highlight the importance of IPC architectural interventions; they can be devised independently of profound knowledge of an emerging pathogen, focusing on technical, constructive, and functional components. These results may inform public health decision-makers and hospital architects on how IPC architectural interventions can be optimally used in healthcare premises.

A quanta-independent approach for the assessment of strategies to reduce the risk of airborne infection

The Wells-Riley model is extensively used for retrospective and prospective modelling of the risk of airborne transmission of infection in indoor spaces. It is also used when examining the efficacy of various removal and deactivation methods for airborne infectious aerosols in the indoor environment, which is crucial when selecting the most effective infection control technologies. The problem is that the large variation in viral load between individuals makes the Wells-Riley model output very sensitive to the input parameters and may yield a flawed prediction of risk. The absolute infection risk estimated with this model can range from nearly 0 % to 100 % depending on the viral load, even when all other factors, such as removal mechanisms and room geometry, remain unchanged. We therefore propose a novel method that removes this sensitivity to viral load. We define a quanta-independent maximum absolute before-after difference in infection risk that is independent of quanta factors like viral load, physical activity, or the dose-response relationships. The input data needed for a non-steady-state calculation are just the removal rates, room volume, and occupancy duration. Under steady-state conditions the approach provides an elegant solution that is only dependent on removal mechanisms before and after applying infection control measures. We applied this method to compare the impact of relative humidity, ventilation rate and its effectiveness, filtering efficiency, and the use of ultraviolet germicidal irradiation on the infection risk. The results demonstrate that the method provides a comprehensive understanding of the impact of infection control strategies on the risk of airborne infection, enabling rational decisions to be made regarding the most effective strategies in a specific context. The proposed method thus provides a practical tool for mitigation of airborne infection risk.

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.

Viral infection transmission and indoor air quality: A systematic review

Respiratory disease transmission in indoor environments presents persistent challenges for health authorities, as exemplified by the recent COVID-19 pandemic. This underscores the urgent necessity to investigate the dynamics of viral infection transmission within indoor environments. This systematic review delves into the methodologies of respiratory infection transmission in indoor settings and explores how the quality of indoor air (IAQ) can be controlled to alleviate this risk while considering the imperative of sustainability. Among the 2722 articles reviewed, 178 were retained based on their focus on respiratory viral infection transmission and IAQ. Fifty eight articles delved into SARS-CoV-2 transmission, 21 papers evaluated IAQ in contexts of other pandemics, 53 papers assessed IAQ during the SARS-CoV-2 pandemic, and 46 papers examined control strategies to mitigate infectious transmission. Furthermore, of the 46 papers investigating control strategies, only nine considered energy consumption. These findings highlight clear gaps in current research, such as analyzing indoor air and surface samples for specific indoor environments, oversight of indoor and outdoor parameters (e.g., temperature, relative humidity (RH), and building orientation), neglect of occupancy schedules, and the absence of considerations for energy consumption while enhancing IAQ. This study distinctly identifies the indoor environmental conditions conducive to the thriving of each respiratory virus, offering IAQ trade-offs to mitigate the risk of dominant viruses at any given time. This study argues that future research should involve digital twins in conjunction with machine learning (ML) techniques. This approach aims to enhance IAQ by analyzing the transmission patterns of various respiratory viruses while considering energy consumption.

The airborne transmission of viruses causes tight transmission bottlenecks

The transmission bottleneck describes the number of viral particles that initiate an infection in a new host. Previous studies have used genome sequence data to suggest that transmission bottlenecks for influenza and SARS-CoV-2 involve few viral particles, but the general principles of virus transmission are not fully understood. Here we show that, across a broad range of circumstances, tight transmission bottlenecks are a simple consequence of the physical process of airborne viral transmission. We use mathematical modelling to describe the physical process of the emission and inhalation of infectious particles, deriving the result that that the great majority of transmission bottlenecks involve few viral particles. While exceptions to this rule exist, the circumstances needed to create these exceptions are likely very rare. We thus provide a physical explanation for previous inferences of bottleneck size, while predicting that tight transmission bottlenecks prevail more generally in respiratory virus transmission.

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.

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.

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.

SARS-CoV-2 airborne infection probability estimated by using indoor carbon dioxide

Airborne transmission is one of the main routes of SARS-CoV-2 spread. It is important to determine the circumstances under which the risk of airborne transmission is increased as well as the effective strategy to reduce such risk. This study aimed to develop a modified version of the Wells-Riley model with indoor CO₂ to estimate the probability of airborne transmission of SARS-CoV-2 Omicron strains with a CO₂ monitor and to evaluate the validity of this model in actual clinical practices. We used the model in three suspected cases of airborne transmission presented to our hospital to confirm its validity. Next, we estimated the required indoor CO₂ concentration at which R₀ does not exceed 1 based on the model. The estimated R₀ (R₀, basic reproduction number) based on the model in each case were 3.19 in three out of five infected patients in an outpatient room, 2.00 in two out of three infected patients in the ward, and 0.191 in none of the five infected patients in another outpatient room. This indicated that our model can estimate R₀ with an acceptable accuracy. In a typical outpatient setting, the required indoor CO₂ concentration at which R₀ does not exceed 1 is below 620 ppm with no mask, 1000 ppm with a surgical mask and 16000 ppm with an N95 mask. In a typical inpatient setting, on the other hand, the required indoor CO₂ concentration is below 540 ppm with no mask, 770 ppm with a surgical mask, and 8200 ppm with an N95 mask. These findings facilitate the establishment of a strategy for preventing airborne transmission in hospitals. This study is unique in that it suggests the development of an airborne transmission model with indoor CO₂ and application of the model to actual clinical practice. Organizations and individuals can efficiently recognize the risk of SARS-CoV-2 airborne transmission in a room and thus take preventive measures such as maintaining good ventilation, wearing masks, or shortening the exposure time to an infected individual by simply using a CO₂ monitor.

Safe CO2 threshold limits for indoor long-range airborne transmission control of COVID-19

CO₂-based infection risk monitoring is highly recommended during the current COVID-19 pandemic. However, the CO₂ monitoring thresholds proposed in the literature are mainly for spaces with fixed occupants. Determining CO₂ threshold is challenging in spaces with changing occupancy due to the co-existence of quanta and CO₂ remaining from previous occupants. Here, we propose a new calculation framework for deriving safe excess CO₂ thresholds (above outdoor level), C _t, for various spaces with fixed/changing occupancy and analyze the uncertainty involved. We categorized common indoor spaces into three scenarios based on their occupancy conditions, e.g., fixed or varying infection ratios (infectors/occupants). We proved that the rebreathed fraction-based model can be applied directly for deriving C _t in the case of a fixed infection ratio (Scenario 1 and Scenario 2). In the case of varying infection ratios (Scenario 3), C _t derivation must follow the general calculation framework due to the existence of initial quanta/excess CO₂. Otherwise, C _t can be significantly biased (e.g., 260 ppm) when the infection ratio varies greatly. C _t can vary significantly based on specific space factors such as occupant number, physical activity, and community prevalence, e.g., 7 ppm for gym and 890 ppm for lecture hall, indicating C _t must be determined on a case-by-case basis. An uncertainty of up to 6 orders of magnitude for C _t was found for all cases due to uncertainty in emissions of quanta and CO₂, thus emphasizing the role of accurate emissions data in determining C _t.

A review on indoor airborne transmission of COVID-19– modelling and mitigation approaches

In the past few years, significant efforts have been made to investigate the transmission of COVID-19. This paper provides a review of the COVID-19 airborne transmission modeling and mitigation strategies. The simulation models here are classified into airborne transmission infectious risk models and numerical approaches for spatiotemporal airborne transmissions. Mathematical descriptions and assumptions on which these models have been based are discussed. Input data used in previous simulation studies to assess the dispersion of COVID-19 are extracted and reported. Moreover, measurements performed to study the COVID-19 airborne transmission within indoor environments are introduced to support validations for anticipated future modeling studies. Transmission mitigation strategies recommended in recent studies have been classified to include modifying occupancy and ventilation operations, using filters and air purifiers, installing ultraviolet (UV) air disinfection systems, and personal protection compliance, such as wearing masks and social distancing. The application of mitigation strategies to various building types, such as educational, office, public, residential, and hospital, is reviewed. Recommendations for future works are also discussed based on the current apparent knowledge gaps covering both modeling and mitigation approaches. Our findings show that different transmission mitigation measures were recommended for various indoor environments; however, there is no conclusive work reporting their combined effects on the level of mitigation that may be achieved. Moreover, further studies should be conducted to understand better the balance between approaches to mitigating the viral transmissions in buildings and building energy consumption.

A CFD-based framework to assess airborne infection risk in buildings

The COVID-19 pandemic has prompted huge efforts to further the scientific knowledge of indoor ventilation and its relationship to airborne infection risk. Exhaled infectious aerosols are spread and inhaled as a result of room airflow characteristics. Many calculation methods and assertions on risk assume 'well-mixed' flow conditions. However, ventilation in buildings is complex and often not showing well-mixed conditions. Ventilation guidance is typically based on the provision of generic minimum ventilation flow rates for a given space, irrespective of the effectiveness in the delivery of the supply air. Furthermore, the airflow might be heavily affected by the season, the HVAC ventilation, or the opening of windows, which would potentially generate draughts and non-uniform conditions. As a result, fresh air concentration would be variable depending upon a susceptible receptor's position in a room and, therefore, associated airborne infection risk. A computational fluid dynamics (CFD) and dynamic thermal modelling (DTM) framework is proposed to assess the influence of internal airflow characteristics on airborne infection risk. A simple metric is proposed, the hourly airborne infection rate (HAI) which can easily help designers to stress-test the ventilation within a building under several conditions. A case study is presented, and the results clearly demonstrate the importance of understanding detailed indoor airflow characteristics and associated concentration patterns in order to provide detailed design guidance, e.g. occupancy, supply air diffusers and furniture layouts, to reduce airborne infection risk.

SARS-CoV-2 Infection and Clinical Signs in Cats and Dogs from Confirmed Positive Households in Germany

On a global scale, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a serious threat to the health of the human population. Not only humans can be infected, but also their companion animals. The antibody status of 115 cats and 170 dogs, originating from 177 German households known to have been SARS-CoV-2 positive, was determined by enzyme-linked immunosorbent assay (ELISA), and the results were combined with information gathered from a questionnaire that was completed by the owner(s) of the animals. The true seroprevalences of SARS-CoV-2 among cats and dogs were 42.5% (95% CI 33.5–51.9) and 56.8% (95% CI 49.1–64.4), respectively. In a multivariable logistic regression accounting for data clustered in households, for cats, the number of infected humans in the household and an above-average contact intensity turned out to be significant risk factors; contact with humans outside the household was a protective factor. For dogs, on the contrary, contact outside the household was a risk factor, and reduced contact, once the human infection was known, was a significant protective factor. No significant association was found between reported clinical signs in animals and their antibody status, and no spatial clustering of positive test results was identified.

Quantifying spatiotemporal variability in occupant exposure to an indoor airborne contaminant with an uncertain source location

Well-mixed zone models are often employed to compute indoor air quality and occupant exposures. While effective, a potential downside to assuming instantaneous, perfect mixing is underpredicting exposures to high intermittent concentrations within a room. When such cases are of concern, more spatially resolved models, like computational-fluid dynamics methods, are used for some or all of the zones. But, these models have higher computational costs and require more input information. A preferred compromise would be to continue with a multi-zone modeling approach for all rooms, but with a better assessment of the spatial variability within a room. To do so, we present a quantitative method for estimating a room's spatiotemporal variability, based on influential room parameters. Our proposed method disaggregates variability into the variability in a room's average concentration, and the spatial variability within the room relative to that average. This enables a detailed assessment of how variability in particular room parameters impacts the uncertain occupant exposures. To demonstrate the utility of this method, we simulate contaminant dispersion for a variety of possible source locations. We compute breathing-zone exposure during the releasing (source is active) and decaying (source is removed) periods. Using CFD methods, we found after a 30 minutes release the average standard deviation in the spatial distribution of exposure was approximately 28% of the source average exposure, whereas variability in the different average exposures was lower, only 10% of the total average. We also find that although uncertainty in the source location leads to variability in the average magnitude of transient exposure, it does not have a particularly large influence on the spatial distribution during the decaying period, or on the average contaminant removal rate. By systematically characterizing a room's average concentration, its variability, and the spatial variability within the room important insights can be gained as to how much uncertainty is introduced into occupant exposure predictions by assuming a uniform in-room contaminant concentration. We discuss how the results of these characterizations can improve our understanding of the uncertainty in occupant exposures relative to well-mixed models.

Measurement and rapid assessment of indoor air quality at mass gathering events to assess ventilation performance and reduce aerosol transmission of SARS-CoV-2

To assess risk factors for COVID-19 transmission and address the closure of mass gathering events since March 2020, the UK Government ran the Events Research Programme (ERP), following which it reopened live events in sports, music, and culture in July 2021. We report the rapid post-occupancy evaluation of Indoor Air Quality (IAQ) and associated long-range airborne transmission risk conducted in the Environmental Study of the ERP. Ten large venues around the UK were monitored with CO2 sensors at a high spatial and temporal resolution during 90 events. An IAQ Index based on CO2 concentration was developed, and all monitored spaces were classified in bands from A to G based on their average and maximum CO2 concentrations from all events. High resolution monitoring and the IAQ Index depicted the overall state of ventilation at live events, and allowed identification of issues with ventilation effectiveness and distribution, and of spaces with poor ventilation and the settings in which long-range airborne transmission risk may be increased. In numerous settings, CO2 concentrations were found to follow patterns relating to event management and specific occupancy of spaces around the venues. Good ventilation was observed in 90% of spaces monitored for given occupancies. Practical applications: High-resolution monitoring of indoor CO2 concentrations is necessary to detect the spatial variation of indoor air quality (IAQ) in large mass gathering event venues. The paper summarises COVID-19 ventilation guidance for buildings and defines a methodology for measurement and rapid assessment of IAQ during occupancy at live events that can be implemented by venue managers. Comparisons of the CO2 concentrations measured during the events identified the spaces at high risk of long-range transmission of airborne pathogens. Building operators should be mindful of the ventilation strategies used relative to the total occupancy in different spaces and the occupant's activities.

Systematic Review of the Key Factors Influencing the Indoor Airborne Spread of SARS-CoV-2

The COVID-19 pandemic due to the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has been plaguing the world since late 2019/early 2020 and has changed the way we function as a society, halting both economic and social activities worldwide. Classrooms, offices, restaurants, public transport, and other enclosed spaces that typically gather large groups of people indoors, and are considered focal points for the spread of the virus. For society to be able to go “back to normal”, it is crucial to keep these places open and functioning. An understanding of the transmission modes occurring in these contexts is essential to set up effective infection control strategies. This understanding was made using a systematic review, according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses statement (PRISMA) 2020 guidelines. We analyze the different parameters influencing airborne transmission indoors, the mathematical models proposed to understand it, and discuss how we can act on these parameters. Methods to judge infection risks through the analysis of the indoor air quality are described. Various mitigation measures are listed, and their efficiency, feasibility, and acceptability are ranked by a panel of experts in the field. Thus, effective ventilation procedures controlled by CO2-monitoring, continued mask wearing, and a strategic control of room occupancy, among other measures, are put forth to enable a safe return to these essential places.

New dose-response model and SARS-CoV-2 quanta emission rates for calculating the long-range airborne infection risk

Predictive models for airborne infection risk have been extensively used during the pandemic, but there is yet still no consensus on a common approach, which may create misinterpretation of results among public health experts and engineers designing building ventilation. In this study we applied the latest data on viral load, aerosol droplet sizes and removal mechanisms to improve the Wells Riley model by introducing the following novelties i) a new model to calculate the total volume of respiratory fluid exhaled per unit time ii) developing a novel viral dose-based generation rate model for dehydrated droplets after expiration iii) deriving a novel quanta-RNA relationship for various strains of SARS-CoV-2 iv) proposing a method to account for the incomplete mixing conditions. These new approaches considerably changed previous estimates and allowed to determine more accurate average quanta emission rates including omicron variant. These quanta values for the original strain of 0.13 and 3.8 quanta/h for breathing and speaking and the virus variant multipliers may be used for simple hand calculations of probability of infection or with developed model operating with six size ranges of aerosol droplets to calculate the effect of ventilation and other removal mechanisms. The model developed is made available as an open-source tool.

Safe distancing in the time of COVID-19

The spread of viruses such as SARS-CoV-2 brought new challenges to our society, including a stronger focus on safety across all businesses. Many countries have imposed a minimum social distance among people in order to ensure their safety. This brings new challenges to many customer-related businesses, such as restaurants, offices, theaters, etc., on how to locate their facilities (tables, seats etc.) under distancing constraints. We propose a parallel between this problem and that of locating wind turbines in an offshore area. The discovery of this parallel allows us to apply Mathematical Optimization algorithms originally designed for wind farms, to produce optimized facility layouts that minimize the overall risk of infection among customers. In this way we can investigate the structure of the safest layouts, with some surprising outcomes. A lesson learned is that, in the safest layouts, the facilities are not equally distanced (as it is typically believed) but tend to concentrate on the border of the available area-a policy that significantly reduces the overall risk of contagion.

Zonal modeling of air distribution impact on the long-range airborne transmission risk of SARS-CoV-2

A widely used analytical model to quantitatively assess airborne infection risk is the Wells-Riley model which is limited to complete air mixing in a single zone. However, this assumption tends not to be feasible (or reality) for many situations. This study aimed to extend the Wells-Riley model so that the infection risk can be calculated in spaces where complete mixing is not present. Some more advanced ventilation concepts create either two horizontally divided air zones in spaces as displacement ventilation or the space may be divided into two vertical zones by downward plane jet as in protective-zone ventilation systems. This is done by evaluating the time-dependent distribution of infectious quanta in each zone and by solving the coupled system of differential equations based on the zonal quanta concentrations. This model introduces a novel approach by estimating the interzonal mixing factor based on previous experimental data for three types of ventilation systems: incomplete mixing ventilation, displacement ventilation, and protective zone ventilation. The modeling approach is applied to a room with one infected and one susceptible person present. The results show that using the Wells-Riley model based on the assumption of completely air mixing may considerably overestimate or underestimate the long-range airborne infection risk in rooms where air distribution is different than complete mixing, such as displacement ventilation, protected zone ventilation, warm air supplied from the ceiling, etc. Therefore, in spaces with non-uniform air distribution, a zonal modeling approach should be preferred in analytical models compared to the conventional single-zone Wells-Riley models when assessing long-range airborne transmission risk of infectious respiratory diseases.

A post-occupancy study of ventilation effectiveness from high-resolution CO2 monitoring at live theatre events to mitigate airborne transmission of SARS-CoV-2

Mass-gathering events were closed around the world in 2020 to minimise the spread of the SARS-CoV-2 virus. Emerging research on the transmission of SARS-CoV-2 emphasised the importance of sufficient ventilation. This paper presents the results of an indoor air quality (IAQ) monitoring study over 82 events in seven mechanically ventilated auditoria to support the UK government Events Research Programme. Indoor carbon dioxide concentration was measured at high resolution before, during, and after occupancy to allow for assessment of the ventilation systems. Generally, good indoor air quality was measured in all auditoria, with average IAQ found to be excellent or very good for 70% of spaces. In some auditoria, spatial variation in IAQ was identified, indicating poor mixing of the air. In addition, surface and air samples were taken and analysed for the presence of bacteria by culture and SARS-CoV-2 using RT-qPCR in one venue. SARS-CoV-2 RNA was detected on a small number of surfaces at very low copy numbers, which are unlikely to pose an infection risk. Under the ventilation strategies and occupancy levels investigated, it is likely that most theatres pose a low risk of long-range transmission of COVID-19.

A population framework for predicting the proportion of people infected by the far-field airborne transmission of SARS-CoV-2 indoors

The number of occupants in a space influences the risk of far-field airborne transmission of SARS-CoV-2 because the likelihood of having infectious and susceptible people both correlate with the number of occupants. This paper explores the relationship between occupancy and the probability of infection, and how this affects an individual person and a population of people. Mass-balance and dose-response models determine far-field transmission risks for an individual person and a population of people after sub-dividing a large reference space into 10 identical comparator spaces. For a single infected person, the dose received by an individual person in the comparator space is 10 times higher because the equivalent ventilation rate per infected person is lower when the per capita ventilation rate is preserved. However, accounting for population dispersion, such as the community prevalence of the virus, the probability of an infected person being present and uncertainty in their viral load, shows the transmission probability increases with occupancy and the reference space has a higher transmission risk. Also, far-field transmission is likely to be a rare event that requires a high emission rate, and there are a set of Goldilocks conditions that are just right when equivalent ventilation is effective at mitigating against transmission. These conditions depend on the viral load, because when they are very high or low, equivalent ventilation has little effect on transmission risk. Nevertheless, resilient buildings should deliver the equivalent ventilation rate required by standards as minimum.

The COVID-19 pandemic: Virus transmission and risk assessment

The coronaviruses are the largest known RNA viruses of which SASR-CoV-2 has been spreading continuously due to its repeated mutation triggered by several environmental factors. Multiple human interventions and lessons learned from the SARS 2002 outbreak helped reduce its spread considerably, and thus, the virus was contained but the emerging mutations burdened the medical facility leading to many deaths in the world. As per the world health organization (WHO) droplet mode transmission is the most common mode of SASR-CoV-2 transmission to which environmental factors including temperature and humidity play a major role. This article highlights the responsibility of environmental causes that would affect the distribution and fate of the virus. Recent development in the risk assessment models is also covered in this article.

Efficacy of single pass UVC air treatment for the inactivation of coronavirus, MS2 coliphage and Staphylococcus aureus bioaerosols

There is strong evidence that SARS-CoV-2 is spread predominantly by airborne transmission, with high viral loads released into the air as respiratory droplets and aerosols from the infected subject. The spread and persistence of SARS-CoV-2 in diverse indoor environments reinforces the urgent need to supplement distancing and PPE based approaches with effective engineering measures for microbial decontamination - thereby addressing the significant risk posed by aerosols. We hypothesized that a portable, single-pass UVC air treatment device (air flow 1254 L/min) could effectively inactivate bioaerosols containing bacterial and viral indicator organisms, and coronavirus without reliance on filtration technology, at reasonable scale. Robust experiments demonstrated UVC dose dependent inactivation of Staphylococcus aureus (UV rate constant (k) = 0.098 m²/J) and bacteriophage MS2, with up to 6-log MS2 reduction achieved in a single pass through the system (k = 0.119 m²/J). The inclusion of a PTFE diffuse reflector increased the effective UVC dose by up to 34% in comparison to a standard Al foil reflector (with identical lamp output), resulting in significant additional pathogen inactivation (1-log S. aureus and MS2, p < 0.001). Complete inactivation of bovine coronavirus bioaerosols was demonstrated through tissue culture infectivity (2.4-log reduction) and RT-qPCR analysis - confirming single pass UVC treatment to effectively deactivate coronavirus to the limit of detection of the culture-based method. Scenario-based modelling was used to investigate the reduction in risk of airborne person-to-person transmission based upon a single infected subject within the small room. Use of the system providing 5 air changes per hour was shown to significantly reduce airborne viral load and maintain low numbers of RNA copies when the infected subject remained in the room, reducing the risk of airborne pathogen transmission to other room users. We conclude that the application of single-pass UVC systems (without reliance on HEPA filtration) could play a critical role in reducing the risk of airborne pathogen transfer, including SARS-CoV2, in locations where adequate fresh air ventilation cannot be implemented.

Modeling the impact of indoor relative humidity on the infection risk of five respiratory airborne viruses

With a modified version of the Wells-Riley model, we simulated the size distribution and dynamics of five airborne viruses (measles, influenza, SARS-CoV-2, human rhinovirus, and adenovirus) emitted from a speaking person in a typical residential setting over a relative humidity (RH) range of 20-80% and air temperature of 20-25 °C. Besides the size transformation of virus-containing droplets due to evaporation, respiratory absorption, and then removal by gravitational settling, the modified model also considered the removal mechanism by ventilation. The trend and magnitude of RH impact depended on the respiratory virus. For rhinovirus and adenovirus humidifying the indoor air from 20/30 to 50% will be increasing the relative infection risk, however, this relative infection risk increase will be negligible for rhinovirus and weak for adenovirus. Humidification will have a potential benefit in decreasing the infection risk only for influenza when there is a large infection risk decrease for humidifying from 20 to 50%. Regardless of the dry solution composition, humidification will overall increase the infection risk via long-range airborne transmission of SARS-CoV-2. Compared to humidification at a constant ventilation rate, increasing the ventilation rate to moderate levels 0.5 → 2.0 h^-1 will have a more beneficial infection risk decrease for all viruses except for influenza. Increasing the ventilation rate from low values of 0.5 h^-1 to higher levels of 6 h^-1 will have a dominating effect on reducing the infection risk regardless of virus type.

A novel CO2-based demand-controlled ventilation strategy to limit the spread of COVID-19 in the indoor environment

Ventilation is of critical importance to containing COVID-19 contagion in indoor environments. Keeping the ventilation rate at high level is recommended by many guidelines to dilute virus-laden respiratory particles and mitigate airborne transmission risk. However, high ventilation rate will cause high energy use. Demand-controlled ventilation is a promising technology option for controlling indoor air quality in an energy-efficient manner. This paper proposes a novel CO₂-based demand-controlled ventilation strategy to limit the spread of COVID-19 in indoor environments. First, the quantitative relationship is established between COVID-19 infection risk and average CO₂ level. Then, a sufficient condition is proposed to ensure COVID-19 event reproduction number is less than 1 under a conservative consideration of the number of infectors. Finally, a ventilation control scheme is designed to make sure the above condition can be satisfied. Case studies of different indoor environments have been conducted on a testbed of a real ventilation system to validate the effectiveness of the proposed strategy. Results show that the proposed strategy can efficiently maintain the reproduction number less than 1 to limit COVID-19 contagion while saving about 30%-50% of energy compared with the fixed ventilation scheme. The proposed strategy offers more practical values compared with existing studies: it is applicable to scenarios where there are multiple infectors, and the number of infectors varies with time; it only requires CO₂ sensors and does not require occupancy detection sensors. Since CO₂ sensors are very mature and low-cost, the proposed strategy is suitable for mass deployment in most existing ventilation systems.

The Built Environment Assessment of Residential Areas in Wuhan during the Coronavirus Disease (COVID-19) Outbreak

The COVID-19 epidemic has emerged as one of the biggest challenges, and the world is focused on preventing and controlling COVID-19. Although there is still insufficient understanding of how environmental conditions may impact the COVID-19 pandemic, airborne transmission is regarded as an important environmental factor that influences the spread of COVID-19. The natural ventilation potential (NVP) is critical for airborne infection control in the micro-built environment, where infectious and susceptible people share air spaces. Taking Wuhan as the research area, we evaluated the NVP in residential areas to combat COVID-19 during the outbreak. We determined four fundamental residential area layouts (point layout, parallel layout, center-around layout, and mixed layout) based on the semantic similarity model for point of interest (POI) picking. Our analyses indicated that the center-around and point layout had a higher NVP, while the mixed and parallel layouts had a lower NVP in winter and spring. Further analysis showed that the proportion of the worst NVP has been rising, while the proportion of the poor NVP remains very high in Wuhan. This study suggested the need to efficiently improve the residential area layout in Wuhan for better urban ventilation to combat COVID-19 without losing other benefits.

Impact of improved indoor environment on recovery from COVID-19 infections: a review of literature

Purpose

This study aims to explore the impact of the indoor environment on recovery from COVID-19 infections. Extant literature on the impact of the four key themes of the indoor environment (indoor air quality, indoor thermal quality, daylighting and visual comfort, and acoustic comfort) on COVID-19 infection and recovery rates were reviewed.

Design/methodology/approach

Data collection for this study was based on extant literature within the Scopus database and scoped to a time frame of 2020–2021 because the topical issue of indoor environmental quality (IEQ) and its impact on COVID-19 arose in the wake of the pandemic. In total, 224 documents were systematically desk reviewed from various journals.

Findings

The study identified that air pollutants such as PM2.5 and PM10 as well as air-conditioned places, low ambient temperatures, poor ventilation and no views of the outdoor environment were deteriorating factors for COVID-19 patients. On the other hand, proper ventilation, the use of air cleaners, views of the outdoor environment and allowance for ample daylighting were improvement factors for COVID-19 patients. The inter-relationship of the various concepts was presented in an ontology chart.

Practical implications

As COVID-19 still exists and keeps evolving, this study provides suggestions to industry professionals, especially health-care Facility Managers, to create a post-pandemic environment focusing on the IEQ and finding long-term and reliable solutions for the well-being of occupants. Adaptability is crucial. New, creative technology solutions are being introduced daily, but it is up to the facility managers and health-care professionals to analyse and specify the most cost- and outcome-effective technologies for their facility.

Originality/value

The study brought to light the pivotal role of the indoor environment on the health and well-being of occupants, particularly in the contraction, spread, prevention and control of infectious diseases such as COVID-19.

Modelling: Understanding pandemics and how to control them

New disease challenges, societal demands and better or novel types of data, drive innovations in the structure, formulation and analysis of epidemic models. Innovations in modelling can lead to new insights into epidemic processes and better use of available data, yielding improved disease control and stimulating collection of better data and new data types. Here we identify key challenges for the structure, formulation, analysis and use of mathematical models of pathogen transmission relevant to current and future pandemics.

Tempo-spatial infection risk assessment of airborne virus via CO2 concentration field monitoring in built environment

The aerosol transmission was academically recognized as a possible transmission route of Coronavirus disease 2019 (COVID-19). We established an approach to assess the indoor tempo-spatial airborne-disease infection risks through aerosol transmission via real-time CO₂ field measurement and occupancy monitoring. Compared to former studies, the proposed method can evaluate real-time airborne disease infection risks through aerosol transmission routes. The approach was utilized in a university office. The accumulated infection risk was calculated for three occupants with practical working schedules (from occupancy recording) and one hypothesis occupant with a typical working schedule. COVID-19 was used as an example. Results demonstrated that the individual infection risks diversified with different dwell times and working places in the office. For the three occupants with a practical working schedule, their 3-day accumulated infection risks were respectively 0.050%, 0.035%, 0.027% and 0.041% due to 11.6, 9.0 and 13.8 h exposure with an initial infector percentage of 1%. The results demonstrate that location and dwell time are both important factors influencing the infection risk of certain occupant in built environment, whereas existing literature seldom took these two points into consideration simultaneously. On the contrary, our proposed approach treated the infection risks as place-by-place, time-by-time and person-by-person diversified in the built environment. The risk assessment results can provide early warning for building occupants and contribute to the transmission control of air-borne disease.

Modeling and experimental study of dispersion and deposition of respiratory emissions with implications for disease transmission

The ability to model the dispersion of pathogens in exhaled breath is important for characterizing transmission of the SARS-CoV-2 virus and other respiratory pathogens. A Computational Fluid Dynamics (CFD) model of droplet and aerosol emission during exhalations has been developed and for the first time compared directly with experimental data for the dispersion of respiratory and oral bacteria from ten subjects coughing, speaking, and singing in a small unventilated room. The modeled exhalations consist of a warm, humid, gaseous carrier flow and droplets represented by a discrete Lagrangian particle phase which incorporates saliva composition. The simulations and experiments both showed greater deposition of bacteria within 1 m of the subject, and the potential for a substantial number of bacteria to remain airborne, with no clear difference in airborne concentration of small bioaerosols (<10 μm diameter) between 1 and 2 m. The agreement between the model and the experimental data for bacterial deposition directly in front of the subjects was encouraging given the uncertainties in model input parameters and the inherent variability within and between subjects. The ability to predict airborne microbial dispersion and deposition gives confidence in the ability to model the consequences of an exhalation and hence the airborne transmission of respiratory pathogens such as SARS-CoV-2.

Practical Indicators for Risk of Airborne Transmission in Shared Indoor Environments and Their Application to COVID-19 Outbreaks

Some infectious diseases, including COVID-19, can undergo airborne transmission. This may happen at close proximity, but as time indoors increases, infections can occur in shared room air despite distancing. We propose two indicators of infection risk for this situation, that is, relative risk parameter (H_r) and risk parameter (H). They combine the key factors that control airborne disease transmission indoors: virus-containing aerosol generation rate, breathing flow rate, masking and its quality, ventilation and aerosol-removal rates, number of occupants, and duration of exposure. COVID-19 outbreaks show a clear trend that is consistent with airborne infection and enable recommendations to minimize transmission risk. Transmission in typical prepandemic indoor spaces is highly sensitive to mitigation efforts. Previous outbreaks of measles, influenza, and tuberculosis were also assessed. Measles outbreaks occur at much lower risk parameter values than COVID-19, while tuberculosis outbreaks are observed at higher risk parameter values. Because both diseases are accepted as airborne, the fact that COVID-19 is less contagious than measles does not rule out airborne transmission. It is important that future outbreak reports include information on masking, ventilation and aerosol-removal rates, number of occupants, and duration of exposure, to investigate airborne transmission.

Practical Indicators for Risk of Airborne Transmission in Shared Indoor Environments and Their Application to COVID-19 Outbreaks

Some infectious diseases, including COVID-19, can undergo airborne transmission. This may happen at close proximity, but as time indoors increases, infections can occur in shared room air despite distancing. We propose two indicators of infection risk for this situation, that is, relative risk parameter (H_r) and risk parameter (H). They combine the key factors that control airborne disease transmission indoors: virus-containing aerosol generation rate, breathing flow rate, masking and its quality, ventilation and aerosol-removal rates, number of occupants, and duration of exposure. COVID-19 outbreaks show a clear trend that is consistent with airborne infection and enable recommendations to minimize transmission risk. Transmission in typical prepandemic indoor spaces is highly sensitive to mitigation efforts. Previous outbreaks of measles, influenza, and tuberculosis were also assessed. Measles outbreaks occur at much lower risk parameter values than COVID-19, while tuberculosis outbreaks are observed at higher risk parameter values. Because both diseases are accepted as airborne, the fact that COVID-19 is less contagious than measles does not rule out airborne transmission. It is important that future outbreak reports include information on masking, ventilation and aerosol-removal rates, number of occupants, and duration of exposure, to investigate airborne transmission.

Control of airborne infectious disease in buildings: Evidence and research priorities

The evolution of SARS-CoV-2 virus has resulted in variants likely to be more readily transmitted through respiratory aerosols, underscoring the increased potential for indoor environmental controls to mitigate risk. Use of tight-fitting face masks to trap infectious aerosol in exhaled breath and reduce inhalation exposure to contaminated air is of critical importance for disease control. Administrative controls including the regulation of occupancy and interpersonal spacing are also important, while presenting social and economic challenges. Indoor engineering controls including ventilation, exhaust, air flow control, filtration, and disinfection by germicidal ultraviolet irradiation can reduce reliance on stringent occupancy restrictions. However, the effects of controls-individually and in combination-on reducing infectious aerosol transfer indoors remain to be clearly characterized to the extent needed to support widespread implementation by building operators. We review aerobiologic and epidemiologic evidence of indoor environmental controls against transmission and present a quantitative aerosol transfer scenario illustrating relative differences in exposure at close-interactive, room, and building scales. We identify an overarching need for investment to implement building controls and evaluate their effectiveness on infection in well-characterized and real-world settings, supported by specific, methodological advances. Improved understanding of engineering control effectiveness guides implementation at scale while considering occupant comfort, operational challenges, and energy costs.

Comparison of COVID-19 infection risks through aerosol transmission in supermarkets and small shops

Aerosol transmission is academically recognized as possible transmission route of Coronavirus disease 2019 (COVID-19). We established an approach to assess the airborne-disease infection risks through aerosol transmission based on the dose-response model and aerosol transport model. The accuracy of evaluation was guaranteed with on-site surveyed ventilation rate and occupant behavior. With the proposed approach, COVID-19 infection risks in 5 typical supermarkets and 21 small shops were evaluated. With one original infected early-shift staff, the average aerosols concentrations at steady-state are 1.06 × 10^-3 RNA copies/m³ in the supermarkets and 4.73 × 10^-2 RNA copies/m³ in the small shops. With the assumption of 5% original infected staff in the retail buildings, the infection probability of one customer is 1.40 × 10^-6 for visiting one small shop and 6.22 × 10^-6 for visiting one supermarket. The averaged infection risk in the supermarkets is higher than the small shops (p-value<0.001). On the other hand, the infection risks are higher for the staff working with the infected staff compared with the customers. The proposed approach can be applied to other occupied buildings and assist the pandemic control policy making for sustainable cities and society.

Implication of coughing dynamics on safe social distancing in an indoor environment-A numerical perspective

Coughing is a primary symptomatic pathway of respiratory or air-borne disease transmission, including COVID-19. Several parameters such as cougher's age, gender, and posture affect particle dispersion indoors. This study numerically investigates the transient cough evolution, contamination range, particle reach probability, and deposition fraction for different age groups of males and females in standing and sitting postures in a ventilated room. The efficacy of a cloth mask has also been studied with and without the influence of air ventilation. Validated Computational Fluid Dynamics methodology has been implemented to model complex physics such as turbulent buoyant cloud, particle-air interaction, particle collision/breakup, and droplet evaporation. Our results show that overall, the contamination range is slightly lower for females due to lower cough velocities and particle counts. Moreover, a significant fraction of particles crosses the two meters social distancing guideline threshold with an unhindered cough. Besides, wearing a cloth mask reduces the average contamination range by approximately two-third of the distance compared to coughing without the mask. However, aerosolized particles reach longer streamwise distances and drift for extended durations beyond thirty seconds. This study can be used to improve the heating, ventilation, and air conditioning recommendations and distancing guidelines in indoor settings.

Multizonal modeling of SARS-CoV-2 aerosol dispersion in a virtual office building

The dispersion of indoor airborne contaminants across different zones within a mechanically ventilated building is a complex phenomenon driven by multiple factors. In this study, we modeled the indoor dispersion of airborne SARS-CoV-2 aerosols within a US Department of Energy detailed medium office prototype building using CONTAM software. The aim of this study is to improve our understanding about how different parts of a building can experience varying concentrations of the airborne viruses under different circumstances of release and mitigation strategies. Results indicate that unventilated stairwells can have significantly higher concentrations of airborne viruses. The mitigation strategies of morning and evening flushing of conditioned zones were not found to be very effective. Instead, a constant high percentage of outdoor air in the supply mix, and the use of masks, portable HEPA air cleaners, MERV 13 or higher HVAC air filters, and ultraviolet germicidal irradiation disinfection were effective strategies to prevent airborne viral contamination in the majority of the simulated office building.

Expert elicitation on the relative importance of possible SARS-CoV-2 transmission routes and the effectiveness of mitigations

OBJECTIVES

To help people make decisions about the most effective mitigation measures against SARS-CoV-2 transmission in different scenarios, the likelihoods of transmission by different routes need to be quantified to some degree (however uncertain). These likelihoods need to be communicated in an appropriate way to illustrate the relative importance of different routes in different scenarios, the likely effectiveness of different mitigation measures along those routes, and the level of uncertainty in those estimates. In this study, a pragmatic expert elicitation was undertaken to supply the underlying quantitative values to produce such a communication tool.

PARTICIPANTS

Twenty-seven individual experts from five countries and many scientific disciplines provided estimates.

OUTCOME MEASURES

Estimates of transmission parameters, assessments of the quality of the evidence, references to relevant literature, rationales for their estimates and sources of uncertainty.

RESULTS AND CONCLUSION

The participants' responses showed that there is still considerable disagreement among experts about the relative importance of different transmission pathways and the effectiveness of different mitigation measures due to a lack of empirical evidence. Despite these disagreements, when pooled, the majority views on each parameter formed an internally consistent set of estimates (for example, that transmission was more likely indoors than outdoors, and at closer range), which formed the basis of a visualisation to help individuals and organisations understand the factors that influence transmission and the potential benefits of different mitigation measures.

Estimating the impact of indoor relative humidity on SARS-CoV-2 airborne transmission risk using a new modification of the Wells-Riley model

A novel modified version of the Wells-Riley model was used to estimate the impact of relative humidity (RH) on the removal of respiratory droplets containing the SARS-CoV-2 virus by deposition through gravitational settling and its inactivation by biological decay; the effect of RH on susceptibility to SARS-CoV-2 was not considered. These effects were compared with the removal achieved by increased ventilation rate with outdoor air. Modeling was performed assuming that the infected person talked continuously for 60 and 120 min. The results of modeling showed that the relative impact of RH on the infection risk depended on the ventilation rate and the size range of virus-laden droplets. A ventilation rate of 0.5 ACH, the change of RH between 20% and 53% was predicted to have a small effect on the infection risk, while at a ventilation rate of 6 ACH this change had nearly no effect. On the contrary, increasing the ventilation rate from 0.5 ACH to 6 ACH was predicted to decrease the infection risk by half which is remarkably larger effect compared with that predicted for RH. It is thus concluded that increasing the ventilation rate is more beneficial for reducing the airborne levels of SARS-CoV-2 than changing indoor RH.

PRACTICAL IMPLICATIONS

The present results show that humidification to moderate levels of 40%-60% RH should not be expected to provide a significant reduction in infection risk caused by SARS-CoV-2, hence installing and running humidifiers may not be an efficient solution to reduce the risk of COVID-19 disease in indoor spaces. The results do however confirm that ventilation has a key role in controlling SARS-CoV-2 virus concentration in the air providing considerably higher benefits. The modified model developed in the present work can be used by public health experts, engineers, and epidemiologists when selecting different measures to reduce the infection risk from SARS-CoV-2 indoors allowing informed decisions concerning indoor environmental control.

COVID-19 and urban spaces: A new integrated CFD approach for public health opportunities

Safe urban public spaces are vital owing to their impacts on public health, especially during pandemics such as the ongoing COVID-19 pandemic. Urban public spaces and urbanscape elements must be designed with the risk of viral transmission in mind. This work therefore examines how the design of urbanscape elements can be revisited to control COVID-19 transmission dynamics. Nine proposed models of urban public seating were thus presented and assessed using a transient three-dimensional computational fluid dynamics (CFD) model, with the Eulerian-Lagrangian method and discrete phase model (DPM). The proposed seating models were evaluated by their impact on the normalized air velocity, the diameter of coughing droplets, and deposition fraction. Each of the proposed models demonstrated an increase in the normalized velocity, and a decrease in the deposition fraction by >29%. Diagonal cross linear and curved triangle configurations demonstrated an improved airflow momentum and turbulent flow, which decreased the droplets deposition fraction by 68%, thus providing an improved, healthier urban public seating option.

Modeling the impacts of physical distancing and other exposure determinants on aerosol transmission

Minimization of airborne virus transmission has become increasingly important due to pandemic and endemic infectious respiratory diseases. Physical distancing is a frequently advocated control measure, but the proximity-based transmission it is intended to control is challenging to incorporate into generalized, ventilation-based models. We utilize a size-dependent aerosol release model with turbulent dispersion to assess the impact of direct, near-field transport in conjunction with changes in ventilation, exposure duration, exhalation/inhalation rates, and masks. We demonstrate this model on indoor and outdoor scenarios to estimate the relative impacts on infection risk. The model can be expressed as a product of six multiplicative factors that may be used to identify opportunities for risk reduction. The additive nature of the short-range (proximity) and long-range (background) transmission components of the aerosol transport factor implies that they must be minimized simultaneously. Indoor simulations showed that close physical distances attenuated the impact of most other risk reduction factors. Increasing ventilation resulted in a 17-fold risk decrease at further physical distances but only a 6-fold decrease at shorter distances. Distance, emission rate, and duration also had large impacts on risk (11-65-fold), while air direction and inhalation rate had lower risk impacts (3-4-fold range). Surgical mask and respirator models predicted higher maximum risk impacts (33- and 280-fold, respectively) than cloth masks (4-fold). Most simulations showed decreasing risk at distances > 1-2 m (3-6 ft). The risk benefit of maintaining 2-m distance vs. 1 m depended substantially on the environmental turbulence and ventilation rate. Outdoors, long-range transmission was negligible and short-range transmission was the primary determinant of risk. Temporary passing events increased risk by up to 50 times at very slow walking speeds and close passing distances, but the relative risks outdoors were still much lower than indoors. The current model assumes turbulent dispersion typical of a given room size and ventilation rate. However, calm environments or confined airflows may increase transmission risks beyond levels predicted with this turbulent model.

Field study to characterize customer flow and ventilation rates in retail buildings in Shenzhen, China

Reduction of the customers' exposure risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the retail buildings, i.e., supermarkets and small shops where residents purchase daily necessities is of prime importance during pandemic. In this study, the main influencing factors of the exposure risk of SARS-CoV-2, namely the occupant density, dwell time, and fresh air volume per person, were on-sited measured in 5 supermarkets and 21 small shops in Shenzhen, China. The small shops with an occupant area per person of 4.7 m²/per presented a more crowded environment than the supermarkets with an occupant area per person of 18.8 m²/per. The average dwell time of customers in the supermarkets linearly increased with the floor area and its probability distribution was fitted well by the Gamma distribution with a shape parameter of 3.0. The average dwell time of customers in the supermarkets was relatively longer than the combination of five types of small shops. In addition, the measured average outdoor air change rate of the small shops by natural ventilation was 10.7 h^-1, while that of the supermarkets by mechanical ventilation was only 0.7 h^-1. Correspondingly, the CO₂ concentration in the small shops was 100-150 ppm lower than the supermarkets. The small shops provided an average fresh air volume per person of 216 m³/(h·per), far exceeding the supermarkets with a value of 95 m³/(h·per).

Transport of Aerosols in Underground Mine Workings in Terms of SARS-CoV-2 Virus Threat

This paper presents a method of implementation and the results of aerosol dispersion tests in underground mine workings. Numerous tests were carried out to determine the potential risk of SARS-CoV-2 coronavirus infection in the underground environment of the mines. The influence of selected parameters of mine air on the possibility and method of aerosol transmission through ventilation routes was experimentally determined in real conditions. The concentration of additional aerosols in the class of ultrafine and fine aerosols increased with the distance from the generator, while the concentration of coarse particles decreased. Assuming the consumption of the solution with which aerosols were generated, even at a small level of 1 cm3/min., the number of additional aerosols was several hundred particles in one cubic centimeter of air at a distance of 50-70 m from the generator. The concentration of ultrafine particles in the range of 40-20,000 nm increased from 122 particles/cm3 to 209 particles/cm3 at air temperature of 12 °C and relative humidity of 95-96%, and from 90 particles/cm3 to 243 particles/cm3 at air temperature of 17 °C and relative humidity of 76-82%, with the increasing distance from the generator (10 m to 50 m).

Viral aerosol transmission of SARS-CoV-2 from simulated human emission in a concert hall

The dispersion of aerosols was studied experimentally in several concert halls to evaluate their airborne route and thus the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreading. For this, a dummy was used that emits simulated human breath containing aerosols (mean diameter of 0.3 μm) and CO2, with a horizontal exhalation velocity of v = 2.4 m/s, measured 10 cm in front of the mouth. Aerosol and CO2 concentration profiles were mapped using sensors placed around the dummy. No substantial enrichment of aerosols and CO2 was found at adjacent seats, provided that (1) there were floor displacement outlets under each seat enabling a minimum local fresh air vertical flow of vv = 0.05 m/s, (2) the air exchange rate (ACH) was more than 3, and (3) the dummy wore a surgical face mask. Knowledge of dispersion of viral droplets by airborne routes in real environments will help in risk assessment when re-opening concert halls and theatres after a pandemic lockdown.

Are Historical Buildings More Adaptive to Minimize the Risks of Airborne Transmission of Viruses and Public Health? A Study of the Hazzazi House in Jeddah (Saudi Arabia)

The coronavirus (COVID-19) pandemic has brought immense challenges to the natural and built environment to develop an antivirus-enabled model for reducing potential risks of spreading the virus at varied scales such as buildings, neighborhoods, and cities. Spatial configurations of structures may hinder or assist the spread of viruses in the built environment. In this study, we have hypothesized that suitable air ventilation in historic buildings may enhance the built environment to combat the spreading of infectious viruses. To provide such quantitative shreds of evidence, we have generated and estimated an integrated model to summarize obtained information by considering natural ventilation, wind speed, inflow and outflow, wind direction, and forecasting the associated risks of airborne disease transmission in a historical building (i.e., the Hazzazi House in particular). Intrinsically, the results have demonstrated that the effectiveness of natural ventilation has directly influenced reducing the risks of transmitting airborne infectious viruses for the selected heritage building in Jeddah (Saudi Arabia). The adopted methods in this research may be useful to understand the potentials of conserving old heritage buildings. Consequently, the results demonstrate that natural air ventilation systems are critical to combat the spread of infectious diseases in the pandemic.

Experimental Investigation of Aerosol and CO2 Dispersion for Evaluation of COVID-19 Infection Risk in a Concert Hall

The dispersion of small aerosols in a concert hall is experimentally studied for estimating the risk of infection with SARS-CoV-2 during a concert. A mannequin was modified to emit an air stream containing aerosols and CO2. The aerosols have a size distribution with a peak diameter (δ) close to 0.3 µm and a horizontal initial particle velocity (vp,x) of 2.4 m/s. The CO2-concentration (c) emitted simultaneously is 7500 ppm. It is investigated, if the spatial dissipation of aerosols and CO2 can be correlated. This would allow the use of technically easier CO2 measurements to monitor compliance with aerosol concentration limits. Both aerosol and CO2 concentrations are mapped by different sensors placed around the mannequin. As a result, no significant enrichment of aerosols and CO2 was obtained outside a radius of 1.5 m when the fresh air ventilation in the concert hall has a steady vertical flow with a velocity of vg,z=0.05 m/s and the installed ventilation system was operating at an air change rate per hour (ACH) of 3, corresponding to an air exchange rate of 51,000 m3/h. A Pearson correlation coefficient of 0.77 was obtained for CO2 and aerosol concentrations measured simultaneously at different positions within the concert hall.