Experimental tularemia in Macaca mulatta: relationship of aerosol particle size to the infectivity of airborne Pasteurella tularensis

Experimental study on the effect of adjacent near-wall heat sources on the particle deposition

Adjacent near-wall heat sources are widely used in indoor environments. It is important to investigate the particle deposition under the influence of coupled thermal plumes arising from adjacent near-wall heat sources to improve indoor air quality and control harmful particle deposition. Thus, this study scrutinizes the behavior of thermal plumes emanating from adjacent near-wall heat sources, focusing on the deposition of particles with diameters of 0.3 μm, 0.5 μm, 1.0 μm and 3.0 μm on the wall behind the heat sources. These findings are juxtaposed with the pattern of particles with varying sizes situated above the single near-wall heat source and away from the heat sources. The study delves into the impact of varying surface temperatures and the distance from the wall behind the heat sources, as well as the top surface of the heat source, on particle deposition in 29 distinct cases. The results indicate that the deposition velocity of particles with the same size is highest above the adjacent near-wall heat sources, followed by that of a single near-wall heat source, and finally, locations away from the near-wall heat source. Also, the decay rate loss coefficient of particles with the same size above the adjacent near-wall heat sources increases with a decrease in the distance of the heat sources from the wall behind them, an increase in the temperature of the heat sources, and a reduction in distance from the top surface of heat sources.

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.

Modelling particle deposition onto surfaces in historic buildings

A comprehensive model of indoor particle deposition onto surfaces of historic interiors was developed. The model takes into account the most important deposition processes observed in historic buildings: Brownian and turbulent diffusion, gravitational settling, turbophoresis, and thermophoresis. The developed model is expressed as a function of important parameters characterizing historic interiors: the friction velocity - capturing the effect of the indoor airflow intensity, the difference between the temperature of the air and the surface, and surface roughness. In particular, a new form of the thermophoretic term was proposed to account for an important mechanism of surface soiling driven by frequent large temperature differences between indoor air and surfaces in historic buildings. The form adopted allowed the temperature gradients to be calculated down to low distances from the surfaces and showed insignificant dependence of the temperature gradient on the diameter of particles, which yielded a meaningful physical description of the process. The predictions of the developed model agreed with the outcome of the previous models, in turn correctly interpreting the experimental data. The model was used in simulating the total deposition velocity in a small-size church taken as an example of a historic building, heated in the cold period. The model adequately predicted the deposition processes and proved to be able to map magnitudes of deposition velocities for specific surface orientations. The crucial effect of the surface roughness on the deposition paths was documented.

Multi-scale risk assessment and mitigations comparison for COVID-19 in urban public transport: A combined field measurement and modeling approach

The outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has caused an unparalleled disruption to daily life. Given that COVID-19 primarily spreads in densely populated indoor areas, urban public transport (UPT) systems pose significant risks. This study presents an analysis of the air change rate in buses, subways, and high speed trains based on measured CO₂ concentrations and passenger behaviors. The resulting values were used as inputs for an infection risk assessment model, which was used to quantitatively evaluate the effects of various factors, including ventilation rates, respiratory activities, and viral variants, on the infection risk. The findings demonstrate that ventilation has a negligible impact on reducing average risks (less than 10.0%) for short-range scales, but can result in a reduction of average risks by 32.1%-57.4% for room scales. When all passengers wear masks, the average risk reduction ranges from 4.5-folds to 7.5-folds. Based on our analysis, the average total reproduction numbers (R) of subways are 1.4-folds higher than buses, and 2-folds higher than high speed trains. Additionally, it is important to note that the Omicron variant may result in a much higher R value, estimated to be approximately 4.9-folds higher than the Delta variant. To reduce disease transmission, it is important to keep the R value below 1. Thus, two indices have been proposed: time-scale based exposure thresholds and spatial-scale based upper limit warnings. Mask wearing provides the greatest protection against infection in the face of long exposure duration to the omicron epidemic.

CO2 concentration as an indicator of indoor ventilation performance to control airborne transmission of SARS-CoV-2

BACKGROUND

The Wells-Riley equation has been extensively used to quantify the infection risk of airborne transmission indoors. This equation is difficult to apply to actual conditions because it requires measurement of the outdoor air supply rate, which vary with time and are difficult to quantify. The method of determining the fraction of inhaled air that has been exhaled previously by someone in a building using a CO₂ concentration measurement can solve the limitations of the existing method. Using this method, the indoor CO₂ concentration threshold can be determined to keep the risk of infection below certain conditions.

METHODS

Based on the calculation of the rebreathed fraction, an appropriate mean indoor CO₂ concentration and required air exchange rate to control SARS-CoV-2 airborne transmission was calculated. The number of indoor occupants, ventilation rate, and the deposition and inactivation rates of the virus-laden aerosols were considered. The application of the proposed indoor CO₂ concentration-based infection rate control was investigated through case studies in school classrooms and restaurants.

RESULTS

In a typical school classroom environment with 20-25 occupants and an exposure time of 6-8 h, the average indoor CO₂ concentration should be kept below 700 ppm to control the risk of airborne infection indoors. The ASHRAE recommended ventilation rate is sufficient when wearing a mask in classrooms. For a typical restaurant with 50-100 occupants and an exposure time of 2-3 h, the average indoor CO₂ concentration should be kept below about 900 ppm. Residence time in the restaurant had a significant effect on the acceptable CO₂ concentration.

CONCLUSION

Given the conditions of the occupancy environment, it is possible to determine an indoor CO₂ concentration threshold, and keeping the CO₂ concentration lower than a certain threshold could help reduce the risk of COVID-19 infection.

Quantitative risk assessment of COVID-19 aerosol transmission indoors: a mechanistic stochastic web application

An increasing body of literature suggests that aerosol inhalation plays a primary role in COVID-19 transmission, particularly in indoor settings. Mechanistic stochastic models can help public health professionals, engineers, and space planners understand the risk of aerosol transmission of COVID-19 to mitigate it. We developed such model and a user-friendly web application to meet the need of accessible risk assessment tools during the COVID-19 pandemic. We built our model based on the Wells-Riley model of respiratory disease transmission, using quanta emission rates obtained from COVID-19 outbreak investigations. In this report, three modelled scenarios were evaluated and compared to epidemiological studies looking at similar settings: classrooms, weddings, and heavy exercise sessions. We found that the risk of long-range aerosol transmission increased 309-332% when people were not wearing masks, and 424-488% when the room was poorly ventilated in addition to no masks being worn across the scenarios. Also, the risk of transmission could be reduced by ∼40-60% with ventilation rates of 5 ACH for 1-4 h exposure events, and ∼70% with ventilation rates of 10 ACH for 4 h exposure events. Relative humidity reduced the risk of infection (inducing viral inactivation) by a maximum of ∼40% in a 4 h exposure event at 70% RH compared to a dryer indoor environment with 25% RH. Our web application has been used by more than 1000 people in 52 countries as of September 1st, 2021. Future work is needed to obtain SARS-CoV-2 dose-response functions for more accurate risk estimates.

Measurement of particulate matter in a heritage building using optical counters: Long-term and spatial analyses

The good conservation of cultural patrimony depends on the quality of the indoor environment where collections and artifacts are kept, being suspended particles one of the key parameters. Among the various methods to study indoor pollution, portable optical counters appear as effective instruments to measure indoor pollution due to their specifications (low visual and acoustic impact). However, it is still one of the least common approaches when assessing the conservation quality in heritage buildings. Therefore, the present study focuses on developing a methodology that uses portable particle counters to monitor particulate matter inside historic buildings and assess indoor conservation quality. Long-term and spatial analyses were conducted using this type of equipment to identify causes of pollution in a case study, the Joanina Library in Coimbra, Portugal. Estimation of night concentrations was carried out as a complementary approach to the monitoring. A new conservation method of classifying indoor pollution was proposed as an alternative to the most common standards. This classification determines four conservation classes (A, B, C, and D) according to particulate matter and the respective percentage of time that measurements are within such classes. As a result, the measurements showed a poor indoor environment quality meeting the requirements of low-level classes, which are those with a greater risk of degradation (Classes C and D). The continuous long-term campaign of four years was decisive for the identification of the main sources and environmental conditions of higher pollution: the exterior pavement, the number of tourists, the use of carpets, and the absence of rain. The spatial results depend on the diameters of the particles and the space's height where the assessment is made. Thus, this type of device and the developed methodology could be used by curators as an effective tool for long-term and spatial assessment in this building typology.

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

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

Assessment of SARS-CoV-2 airborne infection transmission risk in public buses

Public transport environments are thought to play a key role in the spread of SARS-CoV-2 worldwide. Indeed, high crowding indexes (i.e. high numbers of people relative to the vehicle size), inadequate clean air supply, and frequent extended exposure durations make transport environments potential hotspots for transmission of respiratory infections. During the COVID-19 pandemic, generic mitigation measures (e.g. physical distancing) have been applied without also considering the airborne transmission route. This is due to the lack of quantified data about airborne contagion risk in transport environments.

In this study, we apply a novel combination of close proximity and room-scale risk assessment approaches for people sharing public transport environments to predict their contagion risk due to SARS-CoV-2 respiratory infection. In particular, the individual infection risk of susceptible subjects and the transmissibility of SARS-CoV-2 (expressed through the reproduction number) are evaluated for two types of buses, differing in terms of exposure time and crowding index: urban and long-distance buses. Infection risk and reproduction number are calculated for different scenarios as a function of the ventilation rates (both measured and estimated according to standards), crowding indexes, and travel times. The results show that for urban buses, the close proximity contribution significantly affects the maximum occupancy to maintain a reproductive number of <1. In particular, full occupancy of the bus would be permitted only for an infected subject breathing, whereas for an infected subject speaking, masking would be required. For long-distance buses, full occupancy of the bus can be maintained only if specific mitigation solutions are simultaneously applied. For example, for an infected person speaking for 1 h, appropriate filtration of the recirculated air and simultaneous use of FFP2 masks would permit full occupancy of the bus for a period of almost 8 h. Otherwise, a high percentage of immunized persons (>80%) would be needed.

Infection risk in cable cars and other enclosed spaces

As virus-laden aerosols can accumulate and remain suspended for hours in insufficiently ventilated enclosed spaces, indoor environments can heavily contribute to the spreading of airborne infections. In the COVID-19 pandemics, the role possibly played by cable cars has attracted media attention following several outbreaks in ski resort. To assess the real risk of infection, we experimentally characterize the natural ventilation in cable cars and develop a general stochastic model of infection in an arbitrary indoor space that accounts for the epidemiological situation, the virological parameters, and the indoor characteristics (ventilation rate and occupant number density). As a results of the high air exchange rate (we measured up to 180 air changes per hour) and the relatively short duration of the journey, the infection probability in cable cars traveling with open windows is remarkably lower than in other enclosed spaces such as aircraft cabins, train cars, offices, classrooms, and dining rooms. Accounting for the typical duration of the stay, the probability of infection during a cable-car ride is lower by two to three orders of magnitude than in the other examples considered (the highest risk being estimated in case of a private gathering in a poorly ventilated room). For most practical purposes, the infection probability can be approximated by the inhaled viral dose, which provides an upper bound and allows a simple comparison between different indoor situations once the air exchange rate and the occupant number density are known. Our approach and findings are applicable to any indoor space in which the viral transmission is predominately airborne and the air is well mixed.

Impact of air pollution on outdoor cultural heritage objects and decoding the role of particulate matter: a critical review

Atmospheric gases and particulate matter (PM) in contact with the material's surface lead to chemical and physical changes, which in most cases cause degradation of the cultural heritage material. Atmospheric damage and soiling are recognized as two pivotal forms of deterioration of cultural heritage materials caused by air pollution. However, the atmospheric damage effect of PM is rather complicated; its variable composition accelerates the deterioration process. Considering this, one of the important contributions of this work is to review the existing knowledge on PM influence on atmospheric damage, further recognize, and critically evaluate the main gaps in current understanding. The second phenomenon related to cultural heritage material and PM pollution is soiling. Even if soiling was recognized long ago, its definition and knowledge have not changed much for several decades. In the past, it was believed that black carbon (BC) was the primary soiling agent and that the change of the lightness could effectively measure the soiling. With the change of pollution situation, the lightness measurements do not represent the degree of soiling correctly. The additional contribution of this work is thus, the critical evaluation of soiling measurements, and accordingly, due to the change of pollution situation, redefinition of soiling is proposed. Even though numerous studies have treated soiling and atmospheric damage separately, there is an overlap between these two processes. No systematic studies exist on the synergy between soiling and atmospheric damage caused by atmospheric PM.

Characterization of the bioaerosol in a natural thermal cave and assessment of the risk of transmission of SARS-CoV-2 virus

Thermal caves represent an environment characterized by unique chemical/physical properties, often used for treatment and care of musculoskeletal, respiratory, and skin diseases.However, these environments are poorly characterized for their physical and microbiological characteristics; furthermore, the recent pandemic caused by COVID-19 has highlighted the need to investigate the potential transmission scenario of SARS-CoV-2 virus in indoor environments where an in-depth analysis of the aerosol concentrations and dimensional distributions are essential to monitor the spread of the virus.This research work was carried out inside a natural cave located in Viterbo (Terme dei Papi, Italy) where a waterfall of sulfur-sulfate-bicarbonate-alkaline earth mineral thermal water creates a warm-humid environment with 100% humidity and 48 °C temperature. Characterization of the aerosol and bioaerosol was carried out to estimate the personal exposure to aerosol concentrations, as well as particle size distributions, and to give an indication of the native microbial load.The data obtained showed a predominance of particles with a diameter greater than 8 µm, associated with low ability of penetration in the human respiratory system. A low microbial load was also observed, with a prevalence of noncultivable strains generated by the aerosolization of the thermal waters.Finally, the estimation of SARS-CoV-2 infection risk by means of mathematical modeling revealed a low risk of transmission, with a decisive effect given by the mechanical ventilation system, which together with the adoption of social distancing measures makes the risk of infection extremely low.

The Impact of Particulate Matters and Nanoparticles on Thermoplastic Polymer Coatings and Paint Layers

This article attempts to highlight a phenomenon that more or less permanently damages emulsion paint layers, the surfaces of which remain sufficiently permeable for dust particles to become permanently anchored there; when the particles are nanometric, this can cause a permanent change in appearance. Based on scientific documents, empirical observations, laboratory analyses, case studies, and reconstructions of characteristic pictorial layers, this paper aims to highlight the medium- and long-term risks that alter these surfaces, in order to realize strategies for better prevention. The physico-chemical nature of these vulnerable materials will be discussed first, followed by the dust’s involvement; finally, the topic will be illustrated through concrete examples, with photos taken using digital, 4 K optical, and Scanning Electron Microscope equipment (SEM), in order to show how the problem of dust particle accumulation impacts even the most contemporary works of art.

Link between SARS-CoV-2 emissions and airborne concentrations: Closing the gap in understanding

The airborne transmission of SARS-CoV-2 remains surprisingly controversial; indeed, health and regulatory authorities still require direct proof of this mode of transmission. To close this gap, we measured the viral load of SARS-CoV-2 of an infected subject in a hospital room (through an oral and nasopharyngeal swab), as well as the airborne SARS-CoV-2 concentration in the room resulting from the person breathing and speaking. Moreover, we simulated the same scenarios to estimate the concentration of RNA copies in the air through a novel theoretical approach and conducted a comparative analysis between experimental and theoretical results. Results showed that for an infected subject's viral load ranging between 2.4 × 10⁶ and 5.5 × 10⁶ RNA copies mL^-1, the corresponding airborne SARS-CoV-2 concentration was below the minimum detection threshold when the person was breathing, and 16.1 (expanded uncertainty of 32.8) RNA copies m^-3 when speaking. The application of the predictive approach provided concentrations metrologically compatible with the available experimental data (i.e. for speaking activity). Thus, the study presented significant evidence to close the gap in understanding airborne transmission, given that the airborne SARS-CoV-2 concentration was shown to be directly related to the SARS-CoV-2 emitted. Moreover, the theoretical analysis was shown to be able to quantitatively link the airborne concentration to the emission.

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.

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

The COVID-19 pandemic has highlighted the need for a proper risk assessment of respiratory pathogens in indoor settings. This paper documents the COVID Airborne Risk Assessment methodology, to assess the potential exposure of airborne SARS-CoV-2 viruses, with an emphasis on virological and immunological factors in the quantification of the risk. The model results from a multidisciplinary approach linking physical, mechanical and biological domains, enabling decision makers or facility managers to assess their indoor setting. The model was benchmarked against clinical data, as well as two real-life outbreaks, showing good agreement. A probability of infection is computed in several everyday-life settings and with various mitigation measures. The importance of super-emitters in airborne transmission is confirmed: 20% of infected hosts can emit approximately two orders of magnitude more viral-containing particles. The use of masks provides a fivefold reduction in viral emissions. Natural ventilation strategies are very effective to decrease the concentration of virions, although periodic venting strategies are not ideal in certain settings. Although vaccination is an effective measure against hospitalization, their effectiveness against transmission is not optimal, hence non-pharmaceutical interventions (ventilation, masks) should be actively supported. We also propose a critical threshold to define an acceptable risk level.

Prediction and control of aerosol transmission of SARS-CoV-2 in ventilated context: from source to receptor

Global spread of COVID-19 has seriously threatened human life and health. The aerosol transmission route of SARS-CoV-2 is observed often associated with infection clusters under poorly ventilated environment. In the context of COVID-19 pandemic, significant transformation and optimization of traditional ventilation systems are needed. This paper is aimed to offer better understanding and insights into effective ventilation design to maximize its ability in airborne risk control, for particularly the COVID-19. Comprehensive reviews of each phase of aerosol transmission of SARS-CoV-2 from source to receptor are conducted, so as to provide a theoretical basis for risk prediction and control. Infection risk models and their key parameters for risk assessment of SARS-CoV-2 are analyzed. Special focus is given on the efficacy of different ventilation strategies in mitigating airborne transmission. Ventilation interventions are found mainly impacting on the dispersion and inhalation phases of aerosol transmission. The airflow patterns become a key factor in controlling the aerosol diffusion and distribution. Novel and personalized ventilation design, effective integration with other environmental control techniques and resilient HVAC system design to adapt both common and epidemic conditions are still remaining challenging, which need to be solved with the aid of multidisciplinary research and intelligent technologies.

Exploring the potentials of personalized ventilation in mitigating airborne infection risk for two closely ranged occupants with different risk assessment models

In the context of COVID-19, new requirements are occurring in ventilation systems to mitigate airborne transmission risk in indoor environment. Personalized ventilation (PV) which directly delivers clean air to the occupant's breathing zone is considered as a promising solution. To explore the potentials of PV in preventing the spread of infectious aerosols between closely ranged occupants, experiments were conducted with two breathing thermal manikins with three different relative orientations. Nebulized aerosols were used to mimic exhaled droplets transmitted between the occupants. Four risk assessment models were applied to evaluate the exposure or infection risk affected by PV with different operation modes. Results show that PV was effective in reducing the user's infection risk compared with mixing ventilation alone. Relative orientations and operation modes of PV significantly affected its performance in airborne risk control. The infection risk of SARS-CoV-2 was reduced by 65% with PV of 9 L/s after an exposure duration of 2 h back-to-back as assessed by the dose-response model, indicating effective protection effect of PV against airborne transmission. While the side-by-side orientation was found to be the most critical condition for PV in airborne risk control as it would accelerate diffusion of infectious droplets in lateral diffusion to occupants by side. Optimal designs of PV for closely ranged occupants were hereby discussed. The four risk assessment models were compared and validated by experiments with PV, implying basically consistent rules of the predicted risk with PV among the four models. The relevance and applicability of these models were discussed to provide a basis for risk assessment with non-uniformly distributed pathogens indoor.

The vaccination threshold for SARS-CoV-2 depends on the indoor setting and room ventilation

BACKGROUND

Effective vaccines are now available for SARS-CoV-2 in the 2nd year of the COVID-19 pandemic, but there remains significant uncertainty surrounding the necessary vaccination rate to safely lift occupancy controls in public buildings and return to pre-pandemic norms. The aim of this paper is to estimate setting-specific vaccination thresholds for SARS-CoV-2 to prevent sustained community transmission using classical principles of airborne contagion modeling. We calculated the airborne infection risk in three settings, a classroom, prison cell block, and restaurant, at typical ventilation rates, and then the expected number of infections resulting from this risk at varying percentages of occupant immunity.

RESULTS

We estimate the setting-specific immunity threshold for control of wild-type SARS-CoV-2 to range from a low of 40% for a mechanically ventilation classroom to a high of 85% for a naturally ventilated restaurant.

CONCLUSIONS

If vaccination rates are limited to a theoretical minimum of approximately two-thirds of the population, enhanced ventilation above minimum standards for acceptable air quality is needed to reduce the frequency and severity of SARS-CoV-2 superspreading events in high-risk indoor environments.

Factors affecting aerosol SARS-CoV-2 transmission via HVAC systems; a modeling study

The role of heating, ventilation, and air-conditioning (HVAC) systems in the transmission of SARS-CoV-2 is unclear. To address this gap, we simulated the release of SARS-CoV-2 in a multistory office building and three social gathering settings (bar/restaurant, nightclub, wedding venue) using a well-mixed, multi-zone building model similar to those used by Wells, Riley, and others. We varied key factors of HVAC systems, such as the Air Changes Per Hour rate (ACH), Fraction of Outside Air (FOA), and Minimum Efficiency Reporting Values (MERV) to examine their effect on viral transmission, and additionally simulated the protective effects of in-unit ultraviolet light decontamination (UVC) and separate in-room air filtration. In all building types, increasing the ACH reduced simulated infections, and the effects were seen even with low aerosol emission rates. However, the benefits of increasing the fraction of outside air and filter efficiency rating were greatest when the aerosol emission rate was high. UVC filtration improved the performance of typical HVAC systems. In-room filtration in an office setting similarly reduced overall infections but worked better when placed in every room. Overall, we found little evidence that HVAC systems facilitate SARS-CoV-2 transmission; most infections in the simulated office occurred near the emission source, with some infections in individuals temporarily visiting the release zone. HVAC systems only increased infections in one scenario involving a marginal increase in airflow in a poorly ventilated space, which slightly increased the likelihood of transmission outside the release zone. We found that improving air circulation rates, increasing filter MERV rating, increasing the fraction of outside air, and applying UVC radiation and in-room filtration may reduce SARS-CoV-2 transmission indoors. However, these mitigation measures are unlikely to provide a protective benefit unless SARS-CoV-2 aerosol emission rates are high (>1,000 Plaque-forming units (PFU) / min).

Ventilation procedures to minimize the airborne transmission of viruses in classrooms

Reducing the transmission of SARS-CoV-2 through indoor air is the key challenge of the COVID-19 pandemic. Crowded indoor environments, such as schools, represent possible hotspots for virus transmission since the basic non-pharmaceutical mitigation measures applied so far (e.g. social distancing) do not eliminate the airborne transmission mode. There is widespread consensus that improved ventilation is needed to minimize the transmission potential of airborne viruses in schools, whether through mechanical systems or ad-hoc manual airing procedures in naturally ventilated buildings. However, there remains significant uncertainty surrounding exactly what ventilation rates are required, and how to best achieve these targets with limited time and resources. This paper uses a mass balance approach to quantify the ability of both mechanical ventilation and ad-hoc airing procedures to mitigate airborne transmission risk in the classroom environment. For naturally-ventilated classrooms, we propose a novel feedback control strategy using CO₂ concentrations to continuously monitor and adjust the airing procedure. Our case studies show how such procedures can be applied in the real world to support the reopening of schools during the pandemic. Our results also show the inadequacy of relying on absolute CO₂ concentration thresholds as the sole indicator of airborne transmission risk.

Airborne particles and microorganisms in a dental clinic: Variability of indoor concentrations, impact of dental procedures, and personal exposure during everyday practice

This study presents for the first time comprehensive measurements of the particle number size distribution (10 nm to 10 μm) together with next-generation sequencing analysis of airborne bacteria inside a dental clinic. A substantial enrichment of the indoor environment with new particles in all size classes was identified by both activities to background and indoor/outdoor (I/O) ratios. Grinding and drilling were the principal dental activities to produce new particles in the air, closely followed by polishing. Illumina MiSeq sequencing of 16S rRNA of bioaerosol collected indoors revealed the presence of 86 bacterial genera, 26 of them previously characterized as potential human pathogens. Bacterial species richness and concentration determined both by qPCR, and culture-dependent analysis were significantly higher in the treatment room. Bacterial load of the treatment room impacted in the nearby waiting room where no dental procedures took place. I/O ratio of bacterial concentration in the treatment room followed the fluctuation of I/O ratio of airborne particles in the biology-relevant size classes of 1-2.5, 2.5-5, and 5-10 μm. Exposure analysis revealed increased inhaled number of particles and microorganisms during dental procedures. These findings provide a detailed insight on airborne particles of both biotic and abiotic origin in a dental clinic.

High energy efficiency ventilation to limit COVID-19 contagion in school environments

This study investigates the possibility to contain COVID-19 contagion in indoor environments via increasing ventilation rates obtained through high energy efficiency systems combining thermal recovery by heat exchanger and thermodynamic recovery by heat pump. The starting point of this assessment is a procedure to evaluate in naturally ventilated environments, the current infectious risk by using measurements of indoor/outdoor CO₂ concentrations to calculate actual air changes per hour. The method was applied to some typical school environments in Italy. The results indicated very infectious situations with reproduction number R_o values up to exceed 13. But, the simulations assessed an extraordinary reduction of indoor viral concentration and consequently of the infection risk by a strong mechanical ventilation. High ventilation rates make facemasks effective even with use levels (from 50%) reasonable also for pupils. This way, R₀ goes down the value one. As regards energy performance, the behavior of an autonomous high efficiency air handling unit (HEAHU), to be installed in an existing naturally ventilated classroom, was simulated in the monitored days. The results highlight the ability to achieve a reduction in energy consumption between 60% and 72%.

Estimating aerosol transmission risk of SARS-CoV-2 in New York City public schools during reopening

The objective of this study was to estimate the risk of SARS-CoV-2 transmission among students and teachers in New York City public schools, the largest school system in the US. Classroom measurements conducted from December 2017 to September 2018 were used to estimate risk of SARS-CoV-2 transmission using a modified Wells-Riley equation under a steady-state conditions and varying exposure scenarios (infectious student versus teacher, susceptible student versus teacher, with and without masks). We then used multivariable linear regression with GEE to identify school and classroom factors that impact transmission risk. Overall, 101 classrooms in 19 schools were assessed, 86 during the heating season, 69 during cooling season, and 54 during both. The mean probability of transmission was generally low but varied by scenario (range: 0.0015-0.81). Transmission rates were higher during the heating season (beta=0.108, p=0.010), in schools in higher income neighborhoods (>80K versus 20K-40K beta=0.196, p<0.001) and newer buildings (<50 years beta=0.237, p=<0.001; 50-99 years beta=0.230, p=0.013 versus 100+ years) and lower in schools with mechanical ventilation (beta=0.141, p=0.057). Surprisingly, schools located in older buildings and lower-income neighborhoods had lower transmission probabilities, likely due to the greater outdoor airflow associated with an older, non-renovated buildings that allow air to leak in (i.e. drafty buildings). Despite the generally low risk of school-based transmission found in this study, with SARS-CoV-2 prevalence rising in New York City this risk will increase and additional mitigation steps should be implemented in schools now.

The effect of occupant distribution on energy consumption and COVID-19 infection in buildings: A case study of university building

The occupant density in buildings is one of the major and overlooked parameters affecting the energy consumption and virus transmission risk in buildings. HVAC systems energy consumption is highly dependent on the number of occupants. Studies on the transmission of COVID-19 virus have indicated a direct relationship between occupant density and COVID-19 infection risk. This study aims to seek the optimum occupant distribution patterns that account for the lowest number of infected people and minimum energy consumption. A university building located in Tehran has been chosen as a case study, due to its flexibility in performing various occupant distribution patterns. This multi-objective optimization problem, with the objective functions of energy consumption and COVID-19 infected people, is solved by NSGA-II algorithm. Energy consumption is evaluated by EnergyPlus, then it is supplied to the algorithm through a co-simulation communication between EnergyPlus and MATLAB. Results of this optimization algorithm for 5 consequent winter and summer days, represent optimum occupant distribution patterns, associated with minimum energy consumption and COVID-19 infected people for winter and summer. Building air exchange rate, class duration, and working hours of the university, as the COVID-19 controlling approaches were studied, and promising results have been obtained. It was concluded that an optimal population distribution can reduce the number of infected people by up to 56% and energy consumption by 32%. Furthermore, it was concluded that virtual learning is an excellent approach in universities to control the number of infections and energy consumption.

Tracing surface and airborne SARS-CoV-2 RNA inside public buses and subway trains

Given the widespread concern but general lack of information over the possibility of SARS-CoV-2 infection in public transport, key issues such as passenger personal hygiene, efficient air circulation systems, and the effective disinfection of frequently touched surfaces need to be evaluated to educate the public and diminish the risk of viral transmission as we learn to live with the ongoing pandemic. In this context we report on a study involving the collection of 99 samples taken from inside Barcelona buses and subway trains in May to July 2020. From this sample group 82 (58 surface swabs, 9 air conditioning (a/c) filters, 3 a/c dust, 12 ambient air) were selected to be analysed by RT-PCR for traces of the SARS-CoV-2 virus. Thirty of these selected samples showed evidence for one or more of 3 target RNA gene regions specific for this virus (IP2, IP4, E). Most (24) of these 30 samples showed positivity for only 1 of the 3 RNA targets, 4 samples yielded 2 targets, and 2 samples provided evidence for all 3 targets. RNA remnants were more common in surface swabs from support bars (23 out of 58) than in ambient air inside the vehicles (3 out of 12), with relatively higher concentrations of viral RNA fragments in buses rather than in trains. Whereas subway train a/c filters examined were all virus-free, 4 of the 9 bus a/c filter/dust samples yielded evidence for viral RNA. After nocturnal maintenance and cleaning most buses initially yielding positive results subsequently showed elimination of the RT-PCR signal, although signs of viral RNA remained in 4 of 13 initially positive samples. The presence of such remnant viral traces however does not demonstrate infectivity, which in the present study is considered unlikely given the fragmentary nature of the gene targets detected. Nevertheless, best practice demands that close attention to ventilation systems and regular vehicle disinfection in public transport worldwide need to be rigorously applied to be effective at eliminating traces of the virus throughout the vehicle, especially at times when COVID-19 cases are peaking. Additionally, infectivity tests should be implemented to evaluate the efficiency of disinfection procedures to complement the information resulting from RT-PCR analysis. Modelling the probability of infection whilst travelling in buses under different scenarios indicates that forced ventilation greatly reduces the risk.

Quantitative assessment of the risk of airborne transmission of SARS-CoV-2 infection: Prospective and retrospective applications

Airborne transmission is a recognized pathway of contagion; however, it is rarely quantitatively evaluated. The numerous outbreaks that have occurred during the SARS-CoV-2 pandemic are putting a demand on researchers to develop approaches capable of both predicting contagion in closed environments (predictive assessment) and analyzing previous infections (retrospective assessment). This study presents a novel approach for quantitative assessment of the individual infection risk of susceptible subjects exposed in indoor microenvironments in the presence of an asymptomatic infected SARS-CoV-2 subject. The application of a Monte Carlo method allowed the risk for an exposed healthy subject to be evaluated or, starting from an acceptable risk, the maximum exposure time. We applied the proposed approach to four distinct scenarios for a prospective assessment, highlighting that, in order to guarantee an acceptable risk of 10^-3 for exposed subjects in naturally ventilated indoor environments, the exposure time could be well below one hour. Such maximum exposure time clearly depends on the viral load emission of the infected subject and on the exposure conditions; thus, longer exposure times were estimated for mechanically ventilated indoor environments and lower viral load emissions. The proposed approach was used for retrospective assessment of documented outbreaks in a restaurant in Guangzhou (China) and at a choir rehearsal in Mount Vernon (USA), showing that, in both cases, the high attack rate values can be justified only assuming the airborne transmission as the main route of contagion. Moreover, we show that such outbreaks are not caused by the rare presence of a superspreader, but can be likely explained by the co-existence of conditions, including emission and exposure parameters, leading to a highly probable event, which can be defined as a "superspreading event".

An estimation of airborne SARS-CoV-2 infection transmission risk in New York City nail salons

Although airborne transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from person-to-person over long distances is currently thought to be unlikely, the current epidemiological evidence suggests that airborne SARS-CoV-2 infection transmission in confined, indoor spaces is plausible, particularly when outdoor airflow rates are low and when face masks are not utilized. We sought to model airborne infection transmission risk assuming five realistic exposure scenarios using previously estimated outdoor airflow rates for 12 New York City nail salons, a published quanta generation rate specific to SARS-CoV-2, as well as the Wells-Riley equation to assess risk under both steady-state and non-steady-state conditions. Additionally, the impact of face mask-wearing by occupants on airborne infection transmission risk was also evaluated. The risk of airborne infection transmission across all salons and all exposure scenarios when not wearing face masks ranged from <0.015% to 99.25%, with an average airborne infection transmission risk of 24.77%. Wearing face masks reduced airborne infection transmission risk to between <0.01% and 51.96%, depending on the salon, with an average airborne infection transmission risk of 7.30% across all salons. Increased outdoor airflow rates in nail salons were generally strongly correlated with decreased average airborne infection transmission risk. The results of this study indicate that increased outdoor airflow rates and the use of face masks by both employees and customers could substantially reduce SARS-CoV-2 transmission in New York City nail salons. Businesses should utilize multiple layers of infection control measures (e.g. social distancing, face masks, and outdoor airflow) to reduce airborne infection transmission risk for both employees and customers.

Estimation of airborne viral emission: Quanta emission rate of SARS-CoV-2 for infection risk assessment

Airborne transmission is a pathway of contagion that is still not sufficiently investigated despite the evidence in the scientific literature of the role it can play in the context of an epidemic. While the medical research area dedicates efforts to find cures and remedies to counteract the effects of a virus, the engineering area is involved in providing risk assessments in indoor environments by simulating the airborne transmission of the virus during an epidemic. To this end, virus air emission data are needed. Unfortunately, this information is usually available only after the outbreak, based on specific reverse engineering cases. In this work, a novel approach to estimate the viral load emitted by a contagious subject on the basis of the viral load in the mouth, the type of respiratory activity (e.g. breathing, speaking, whispering), respiratory physiological parameters (e.g. inhalation rate), and activity level (e.g. resting, standing, light exercise) is proposed. The results showed that high quanta emission rates (>100 quanta h^-1) can be reached by an asymptomatic infectious SARS-CoV-2 subject performing vocalization during light activities (i.e. walking slowly) whereas a symptomatic SARS-CoV-2 subject in resting conditions mostly has a low quanta emission rate (<1 quantum h^-1). The findings in terms of quanta emission rates were then adopted in infection risk models to demonstrate its application by evaluating the number of people infected by an asymptomatic SARS-CoV-2 subject in Italian indoor microenvironments before and after the introduction of virus containment measures. The results obtained from the simulations clearly highlight that a key role is played by proper ventilation in containment of the virus in indoor environments.

Estimation of airborne viral emission: Quanta emission rate of SARS-CoV-2 for infection risk assessment

Airborne transmission is a pathway of contagion that is still not sufficiently investigated despite the evidence in the scientific literature of the role it can play in the context of an epidemic. While the medical research area dedicates efforts to find cures and remedies to counteract the effects of a virus, the engineering area is involved in providing risk assessments in indoor environments by simulating the airborne transmission of the virus during an epidemic. To this end, virus air emission data are needed. Unfortunately, this information is usually available only after the outbreak, based on specific reverse engineering cases. In this work, a novel approach to estimate the viral load emitted by a contagious subject on the basis of the viral load in the mouth, the type of respiratory activity (e.g. breathing, speaking, whispering), respiratory physiological parameters (e.g. inhalation rate), and activity level (e.g. resting, standing, light exercise) is proposed. The results showed that high quanta emission rates (>100 quanta h^-1) can be reached by an asymptomatic infectious SARS-CoV-2 subject performing vocalization during light activities (i.e. walking slowly) whereas a symptomatic SARS-CoV-2 subject in resting conditions mostly has a low quanta emission rate (<1 quantum h^-1). The findings in terms of quanta emission rates were then adopted in infection risk models to demonstrate its application by evaluating the number of people infected by an asymptomatic SARS-CoV-2 subject in Italian indoor microenvironments before and after the introduction of virus containment measures. The results obtained from the simulations clearly highlight that a key role is played by proper ventilation in containment of the virus in indoor environments.