Modelling airborne transmission of SARS-CoV-2 using CARA: risk assessment for enclosed spaces

An integrated airborne transmission risk assessment model for respiratory viruses: short- and long-range contributions

This study presents an advanced airborne transmission risk assessment model that integrates both short- and long-range routes in the spread of respiratory viruses, building upon the CERN Airborne Model for Indoor Risk Assessment (CAiMIRA) and aligned with the new World Health Organization (WHO) terminology. Thanks to a two-stage exhaled jet approach, the model accurately simulates short-range exposures, thereby improving infection risk predictions across diverse indoor settings. Key findings reveal that in patient wards, the short-range viral dose is 10-fold higher than the long-range component, highlighting the critical role of close proximity interactions. Implementation of FFP2 respirators resulted in a remarkable 13-fold reduction in viral dose, underscoring the effectiveness of personal protective equipment (PPE). Additionally, the model demonstrated that an 8 h exposure in a poorly ventilated office can equate to the risk of a 15 min face-to-face, mask-less interaction, emphasizing the importance of physical distancing and source control. We also found in high-risk or low-occupancy settings, that secondary transmission is driven more by overall epidemic trends than by the presence of individual superspreaders. Monte Carlo simulations across various scenarios, including classrooms and offices, validate the model's robustness in optimizing infection prevention strategies. These findings support targeted interventions for short- and long-range exposure to reduce airborne transmission.

Quantifying multi-virion aerosols in respiratory infection transmission

Infectious aerosols are expired in various sizes, and the number of contained virions is expected to significantly vary among expired aerosols. To evaluate the effect of the number of contained virions on infection risk, multi-virion aerosols in expired air should be first quantified. In this study, we categorised expired aerosols into traditional aerosol size bins and aerosols containing different number of virions. We quantified the number of virions in aerosols of each size bin and estimated the size distribution of aerosols which contain a certain number of virions when the viral load is known. This analysis helped us to determine the relationship between multi-size aerosols and multi-virion aerosols. Our findings indicate that for long-range airborne transmission, the airborne transmission droplets derived from four COVID-19 outbreak venues contain at most one infectious virion, supporting the one-virion assumption for the considered viral load ranges. However, for short-range airborne transmission, the impact of multi-virion aerosols on infection risk must be considered. Our quantification of multi-virion aerosols for the first time lays the groundwork for incorporating the multi-virion assumption into infection risk assessments.

Loop-Mediated Isothermal Amplification (LAMP): An Innovative Approach for the Environmental Monitoring of SARS-CoV-2

The rapid and accurate detection of SARS-CoV-2 in environmental settings is crucial for effective public health management during the COVID-19 pandemic. This study compares the performance of the Reverse Transcription quantitative polymerase chain reaction (RT-qPCR) and the Reverse Transcription loop-mediated isothermal amplification (RT-LAMP) for SARS-CoV-2 detection from 100 surface samples collected in healthcare environments. The reference method, RT-qPCR, identified a percentage of 25% of positive samples, while RT-LAMP detected a percentage of 27% of positive surfaces. Our findings reveal a sensitivity of 32% and specificity of 75% for RT-LAMP, with a positive predictive value of 30% and a negative predictive value of 77%. The overall accuracy and concordance with RT-qPCR was 64% for both methods. Despite its lower sensitivity compared to RT-qPCR, RT-LAMP had an advantage due to its rapid screening and environmental surveillance, which is particularly useful for confirming negative results. These results underscore the potential of RT-LAMP not only as a valuable method in the environmental monitoring of SARS-CoV-2 but also as a system to control the sanitation process in ordinary and emergency conditions, providing further optimization and validation for its reliability in routine surveillance and outbreak response efforts.

Aerosolization ocular surface microorganisms accumulation effect during non-contact tonometer measurements

PURPOSE

This study aimed to verify that aerosolization ocular surface microorganisms (AOSMs) accumulated during non-contact tonometry (NCT) measurements.

METHODS

A total of 508 participants (740 eyes) were enrolled in the study. In Experiment 1, before NCT was performed on each eye, the air was disinfected, and environment air control samples were collected via Air ideal® 3P (Bio Merieux). During NCT measurements, microbial aerosol samples were collected once from each eye. In Experiment 2, we collected initial blank control samples and then repeated Experiment 1. Finally, in Experiment 3, after the background microbial aerosol investigation, we cumulatively sampled AOSMs from each 10 participants then culture once, without any interventions to interrupt the accumulation. The collected samples were incubated and identified using matrix-assisted laser desorption/ ionization time-of-flight mass spectrometry (MALDI-TOF-MS).

RESULTS

Pathogenic Aerococcus viridans and other microorganisms from human eyes can spread and accumulate in the air during NCT measurements. The species and quantity of AOSMs produced by NCT measurements can demonstrate an accumulation effect.

CONCLUSION

AOSMs generated during NCT measurements are highly likely to spread and accumulate in the air, thereby may increase the risk of exposure to and transmission of bio-aerosols.

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.

AI-Enhanced Tools and Strategies for Airborne Disease Prevention in Cultural Heritage Sites

In the wake of the COVID-19 pandemic, the surveillance and safety measures of indoor Cultural Heritage sites have become a paramount concern due to the unique challenges posed by their enclosed environments and high visitor volumes. This communication explores the integration of Artificial Intelligence (AI) in enhancing epidemiological surveillance and health safety protocols in these culturally significant spaces. AI technologies, including machine learning algorithms and Internet of Things (IoT) sensors, have shown promising potential in monitoring air quality, detecting pathogens, and managing crowd dynamics to mitigate the spread of infectious diseases. We review various applications of AI that have been employed to address both direct health risks and indirect impacts such as visitor experience and preservation practices. Additionally, this paper discusses the challenges and limitations of AI deployment, such as ethical considerations, privacy issues, and financial constraints. By harnessing AI, Cultural Heritage sites can not only improve their resilience against future pandemics but also ensure the safety and well-being of visitors and staff, thus preserving these treasured sites for future generations. This exploration into AI's role in post-COVID surveillance at Cultural Heritage sites opens new frontiers in combining technology with traditional conservation and public health efforts, providing a blueprint for enhanced safety and operational efficiency in response to global health challenges.

A COVID-19 cluster analysis in an office: Assessing the long-range aerosol and fomite transmissions with infection control measures

Simulated exposure to severe acute respiratory syndrome coronavirus 2 in the environment was demonstrated based on the actual coronavirus disease 2019 cluster occurrence in an office, with a projected risk considering the likely transmission pathways via aerosols and fomites. A total of 35/85 occupants were infected, with the attack rate in the first stage as 0.30. It was inferred that the aerosol transmission at long-range produced the cluster at virus concentration in the saliva of the infected cases on the basis of the simulation, more than 108 PFU mL-1. Additionally, all wearing masks effectiveness was estimated to be 61%-81% and 88%-95% reduction in risk for long-range aerosol transmission in the normal and fit state of the masks, respectively, and a 99.8% or above decline in risk of fomite transmission. The ventilation effectiveness for long-range aerosol transmission was also calculated to be 12%-29% and 36%-66% reductions with increases from one air change per hour (ACH) to two ACH and six ACH, respectively. Furthermore, the virus concentration reduction in the saliva to 1/3 corresponded to the risk reduction for long-range aerosol transmission by 60%-64% and 40%-51% with and without masks, respectively.

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.

Applications of Quantitative Microbial Risk Assessment to Respiratory Pathogens and Implications for Uptake in Policy: A State-of-the-Science Review

BACKGROUND

Respiratory tract infections are major contributors to the global disease burden. Quantitative microbial risk assessment (QMRA) holds potential as a rapidly deployable framework to understand respiratory pathogen transmission and inform policy on infection control.

OBJECTIVES

The goal of this paper was to evaluate, motivate, and inform further development of the use of QMRA as a rapid tool to understand the transmission of respiratory pathogens and improve the evidence base for infection control policies.

METHODS

We conducted a literature review to identify peer-reviewed studies of complete QMRA frameworks on aerosol inhalation or contact transmission of respiratory pathogens. From each of the identified studies, we extracted and summarized information on the applied exposure model approaches, dose-response models, and parameter values, including risk characterization. Finally, we reviewed linkages between model outcomes and policy.

RESULTS

We identified 93 studies conducted in 16 different countries with complete QMRA frameworks for diverse respiratory pathogens, including SARS-CoV-2, Legionella spp., Staphylococcus aureus, influenza, and Bacillus anthracis. Six distinct exposure models were identified across diverse and complex transmission pathways. In 57 studies, exposure model frameworks were informed by their ability to model the efficacy of potential interventions. Among interventions, masking, ventilation, social distancing, and other environmental source controls were commonly assessed. Pathogen concentration, aerosol concentration, and partitioning coefficient were influential exposure parameters as identified by sensitivity analysis. Most (84%, n = 78 ) studies presented policy-relevant content including a) determining disease burden to call for policy intervention, b) determining risk-based threshold values for regulations, c) informing intervention and control strategies, and d) making recommendations and suggestions for QMRA application in policy.

CONCLUSIONS

We identified needs to further the development of QMRA frameworks for respiratory pathogens that prioritize appropriate aerosol exposure modeling approaches, consider trade-offs between model validity and complexity, and incorporate research that strengthens confidence in QMRA results. https://doi.org/10.1289/EHP12695.

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

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

Informing Building Strategies to Reduce Infectious Aerosol Transmission Risk by Integrating DNA Aerosol Tracers with Quantitative Microbial Risk Assessment

Using aerosol-based tracers to estimate risk of infectious aerosol transmission aids in the design of buildings with adequate protection against aerosol transmissible pathogens, such as SARS-CoV-2 and influenza. We propose a method for scaling a SARS-CoV-2 bulk aerosol quantitative microbial risk assessment (QMRA) model for impulse emissions, coughing or sneezing, with aerosolized synthetic DNA tracer concentration measurements. With point-of-emission ratios describing relationships between tracer and respiratory aerosol emission characteristics (i.e., volume and RNA or DNA concentrations) and accounting for aerosolized pathogen loss of infectivity over time, we scale the inhaled pathogen dose and risk of infection with time-integrated tracer concentrations measured with a filter sampler. This tracer-scaled QMRA model is evaluated through scenario testing, comparing the impact of ventilation, occupancy, masking, and layering interventions on infection risk. We apply the tracer-scaled QMRA model to measurement data from an ambulatory care room to estimate the risk reduction resulting from HEPA air cleaner operation. Using DNA tracer measurements to scale a bulk aerosol QMRA model is a relatively simple method of estimating risk in buildings and can be applied to understand the impact of risk mitigation efforts.

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.

Respiratory aerosol particle emission and simulated infection risk is greater during indoor endurance than resistance exercise

Pathogens such as severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), influenza, and rhinoviruses are transmitted by airborne aerosol respiratory particles that are exhaled by infectious subjects. We have previously reported that the emission of aerosol particles increases on average 132-fold from rest to maximal endurance exercise. The aims of this study are to first measure aerosol particle emission during an isokinetic resistance exercise at 80% of the maximal voluntary contraction until exhaustion, second to compare aerosol particle emission during a typical spinning class session versus a three-set resistance training session. Finally, we then used this data to calculate the risk of infection during endurance and resistance exercise sessions with different mitigation strategies. During a set of isokinetic resistance exercise, aerosol particle emission increased 10-fold from 5,400 ± 1,200 particles/min at rest to 59,000 ± 69,900 particles/min during a set of resistance exercise. We found that aerosol particle emission per minute is on average 4.9-times lower during a resistance training session than during a spinning class. Using this data, we determined that the simulated infection risk increase during an endurance exercise session was sixfold higher than during a resistance exercise session when assuming one infected participant in the class. Collectively, this data helps to select mitigation measures for indoor resistance and endurance exercise classes at times where the risk of aerosol-transmitted infectious disease with severe outcomes is high.

Overview of the Role of Spatial Factors in Indoor SARS-CoV-2 Transmission: A Space-Based Framework for Assessing the Multi-Route Infection Risk

The COVID-19 pandemic has lasted from 2019 to 2022, severely disrupting human health and daily life. The combined effects of spatial, environmental, and behavioral factors on indoor COVID-19 spread and their interactions are usually ignored. Especially, there is a lack of discussion on the role of spatial factors in reducing the risk of virus transmission in complex and diverse indoor environments. This paper endeavours to summarize the spatial factors and their effects involved in indoor virus transmission. The process of release, transport, and intake of SARS-CoV-2 was reviewed, and six transmission routes according to spatial distance and exposure way were classified. The triangular relationship between spatial, environmental and occupant behavioral parameters during virus transmission was discussed. The detailed effects of spatial parameters on droplet-based, surface-based and air-based transmission processes and virus viability were summarized. We found that spatial layout, public-facility design and openings have a significant indirect impact on the indoor virus distribution and transmission by affecting occupant behavior, indoor airflow field and virus stability. We proposed a space-based indoor multi-route infection risk assessment framework, in which the 3D building model containing detailed spatial information, occupant behavior model, virus-spread model and infection-risk calculation model are linked together. It is also applicable to other, similar, respiratory infectious diseases such as SARS, influenza, etc. This study contributes to developing building-level, infection-risk assessment models, which could help building practitioners make better decisions to improve the building's epidemic-resistance performance.

A comprehensive modelling approach to estimate the transmissibility of coronavirus and its variants from infected subjects in indoor environments

A central issue in assessing the airborne risk of COVID-19 infections in indoor spaces pertains to linking the viral load in infected subjects to the lung deposition probability in exposed individuals through comprehensive aerosol dynamics modelling. In this paper, we achieve this by combining aerosol processes (evaporation, dispersion, settling, lung deposition) with a novel double Poisson model to estimate the probability that at least one carrier particle containing at least one virion will be deposited in the lungs and infect a susceptible individual. Multiple emission scenarios are considered. Unlike the hitherto used single Poisson models, the double Poisson model accounts for fluctuations in the number of carrier particles deposited in the lung in addition to the fluctuations in the virion number per carrier particle. The model demonstrates that the risk of infection for 10-min indoor exposure increases from 1 to 50% as the viral load in the droplets ejected from the infected subject increases from 2 × 108 to 2 × 1010 RNA copies/mL. Being based on well-established aerosol science and statistical principles, the present approach puts airborne risk assessment methodology on a sound formalistic footing, thereby reducing avoidable epistemic uncertainties in estimating relative transmissibilities of different coronavirus variants quantified by different viral loads.

SARS-CoV-2 aerosol transmission in schools: the effectiveness of different interventions

BACKGROUND

Indoor aerosol transmission of SARS-CoV-2 has been widely recognised, especially in schools where children remain in closed indoor spaces and largely unvaccinated. Measures such as strategic natural ventilation and high efficiency particulate air (HEPA) filtration remain poorly implemented and mask mandates are often progressively lifted as vaccination rollout is enhanced.

METHODS

We adapted a previously developed aerosol transmission model to study the effect of interventions (natural ventilation, face masks, HEPA filtration and their combinations) on the concentration of virus particles in a classroom of 160 m3 containing one infectious individual. The cumulative dose of viruses absorbed by exposed occupants was calculated.

RESULTS

In the absence of interventions, the cumulative dose absorbed was 1.5 times higher in winter than in spring/summer, increasing chances of indoor airborne transmission in winter. However, natural ventilation was more effective in winter, leading to up to a 20-fold decrease in cumulative dose when six windows were fully open at all times. In winter, partly opening two windows all day or fully opening six windows at the end of each class was effective as well (2.7- to 3-fold decrease). In summer, good ventilation levels could be achieved through the opening of windows all day long (2- to 7-fold decrease depending on the number of windows open). Opening windows only during yard and lunch breaks had minimal effect (≤1.5-fold decrease). One HEPA filter was as effective as two windows partly open all day in winter (3-fold decrease) whereas two filters were more effective (5-fold decrease). Surgical face masks were very effective independently of the season (8-fold decrease). Combined interventions (i.e., natural ventilation, masks, and HEPA filtration) were the most effective (≥25-fold decrease) and remained highly effective in the presence of a super-spreader.

INTERPRETATION

Natural ventilation, face masks, and HEPA filtration are effective interventions to reduce SARS-CoV-2 aerosol transmission. These measures should be combined and complemented by additional interventions (e.g., physical distancing, hygiene, testing, contact tracing and vaccination) to maximise benefit.

Dynamics of SARS-CoV-2 spreading under the influence of environmental factors and strategies to tackle the pandemic: A systematic review

COVID-19 is deemed as the most critical world health calamity of the 21st century, leading to dramatic life loss. There is a pressing need to understand the multi-stage dynamics, including transmission routes of the virus and environmental conditions due to the possibility of multiple waves of COVID-19 in the future. In this paper, a systematic examination of the literature is conducted associating the virus-laden-aerosol and transmission of these microparticles into the multimedia environment, including built environments. Particularly, this paper provides a critical review of state-of-the-art modelling tools apt for COVID-19 spread and transmission pathways. GIS-based, risk-based, and artificial intelligence-based tools are discussed for their application in the surveillance and forecasting of COVID-19. Primary environmental factors that act as simulators for the spread of the virus include meteorological variation, low air quality, pollen abundance, and spatial-temporal variation. However, the influence of these environmental factors on COVID-19 spread is still equivocal because of other non-pharmaceutical factors. The limitations of different modelling methods suggest the need for a multidisciplinary approach, including the 'One-Health' concept. Extended One-Health-based decision tools would assist policymakers in making informed decisions such as social gatherings, indoor environment improvement, and COVID-19 risk mitigation by adapting the control measurements.

Risk of SARS-CoV-2 in a car cabin assessed through 3D CFD simulations

In this study, the risk of infection from SARS-CoV-2 Delta variant of passengers sharing a car cabin with an infected subject for a 30-min journey is estimated through an integrated approach combining a recently developed predictive emission-to-risk approach and a validated CFD numerical model numerically solved using the open-source OpenFOAM software. Different scenarios were investigated to evaluate the effect of the infected subject position within the car cabin, the airflow rate of the HVAC system, the HVAC ventilation mode, and the expiratory activity (breathing vs. speaking). The numerical simulations here performed reveal that the risk of infection is strongly influenced by several key parameters: As an example, under the same ventilation mode and emitting scenario, the risk of infection ranges from zero to roughly 50% as a function of the HVAC flow rate. The results obtained also demonstrate that (i) simplified zero-dimensional approaches limit proper evaluation of the risk in such confined spaces, conversely, (ii) CFD approaches are needed to investigate the complex fluid dynamics in similar indoor environments, and, thus, (iii) the risk of infection in indoor environments characterized by fixed seats can be in principle controlled by properly designing the flow patterns of the environment.

The role of SARS-CoV-2 aerosol transmission during the COVID-19 pandemic

The COVID-19 pandemic, caused by the virus SARS-CoV-2, has touched most parts of the world and devastated the lives of many. The high transmissibility coupled with the initial poor outcome for the elderly led to crushingly high fatalities. The scientific response to the pandemic has been formidable, aided by advancements in virology, computing, data analysis, instrumentation, diagnostics, engineering and infection control. This has led to improvements in understanding and has helped to challenge some established orthodoxies. Sufficient time has elapsed since the start of the COVID-19 pandemic that a clearer view has emerged about transmission and infection risks, public health responses and related societal and economic impacts. This timely volume has provided an opportunity for the science community to report on these new developments.