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

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.

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.

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.

Energy, economic, and environmental impacts of enhanced ventilation strategies on railway coaches to reduce Covid-19 contagion risks

In the last years, the Covid-19 outbreak raised great awareness about ventilation system performance in confined spaces. Specifically, the heating, ventilation, and air conditioning system design and operating parameters, such as air change per hour, air recirculation ratio, filtration device performance, and vents location, play a crucial role in reducing the spread of viruses, moulds, bacteria, and general pollutants. Concerning the transport sector, due to the impracticability of social distancing, and the relatively loose requirements of ventilation standards, the SARS-COV-19 outbreak brought a reduction of payload (up to 50%) for different carriers. Specifically, this has been particularly severe for the railway sector, where train coaches are typically characterized by relatively elevated occupancy and high recirculation ratios. In this framework, to improve the Indoor Air Quality and reduce the Covid-19 contagion risk in railway carriages, the present paper investigates the energy, economic and environmental feasibility of diverse ventilation strategies. To do so, a novel dynamic simulation tool for the complete dynamic performance investigation of trains was developed in an OpenStudio environment. To assess the Covid-19 contagion risk connected to the investigated scenarios, the Wells-Riley model has been adopted. To prove the proposed approach's capabilities and show the Covid-19 infection risk reduction potentially achievable by varying the adopted ventilation strategies, a suitable case study related to an existing medium-distance train operating in South/Central Italy is presented. The conducted numerical simulations return interesting results providing also useful design criteria.

Impact of mechanical ventilation control strategies based on non-steady-state and steady-state Wells-Riley models on airborne transmission and building energy consumption

Ventilation is an effective solution for improving indoor air quality and reducing airborne transmission. Buildings need sufficient ventilation to maintain a low infection risk but also need to avoid an excessive ventilation rate, which may lead to high energy consumption. The Wells-Riley (WR) model is widely used to predict infection risk and control the ventilation rate. However, few studies compared the non-steady-state (NSS) and steady-state (SS) WR models that are used for ventilation control. To fill in this research gap, this study investigates the effects of the mechanical ventilation control strategies based on NSS/SS WR models on the required ventilation rates to prevent airborne transmission and related energy consumption. The modified NSS/SS WR models were proposed by considering many parameters that were ignored before, such as the initial quantum concentration. Based on the NSS/SS WR models, two new ventilation control strategies were proposed. A real building in Canada is used as the case study. The results indicate that under a high initial quantum concentration (e.g., 0.3 q/m³) and no protective measures, SS WR control underestimates the required ventilation rate. The ventilation energy consumption of NSS control is up to 2.5 times as high as that of the SS control.

Measuring Work-related Risk of Coronavirus Disease 2019 (COVID-19): Comparison of COVID-19 Incidence by Occupation and Industry-Wisconsin, September 2020 to May 2021

BACKGROUND

Work-related exposures play an important role in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, yet few studies have compared SARS-CoV-2 expsoure risk across occupations and industries.

METHODS

During September 2020 to May 2021, the Wisconsin Department of Health Services collected occupation and industry data as part of routine coronavirus disease 2019 (COVID-19) case investigations. Adults aged 18-64 years with confirmed or probable COVID-19 in Wisconsin were assigned standardized occupation and industry codes. Cumulative incidence rates were weighted for non-response and calculated using full-time equivalent (FTE) workforce denominators from the 2020 American Community Survey.

RESULTS

An estimated 11.6% of workers (347 013 of 2.98 million) in Wisconsin, ages 18-64 years, had COVID-19 from September 2020 to May 2021. The highest incidence by occupation (per 100 FTE) occurred among personal care and services workers (22.1), healthcare practitioners and support staff (20.7), and protective services workers (20.7). High-risk sub-groups included nursing assistants and personal care aides (28.8), childcare workers (25.8), food and beverage service workers (25.3), personal appearance workers (24.4), and law enforcement workers (24.1). By industry, incidence was highest in healthcare (18.6); the highest risk sub-sectors were nursing care facilities (30.5) and warehousing (28.5).

CONCLUSIONS

This analysis represents one of the most complete examinations to date of COVID-19 incidence by occupation and industry. Our approach demonstrates the value of standardized occupational data collection by public health and may be a model for improved occupational surveillance elsewhere. Workers at higher risk of SARS-CoV-2 exposure may benefit from targeted workplace COVID-19 vaccination and mitigation efforts.

Ventilation strategies and design impacts on indoor airborne transmission: A review

The COVID-19 outbreak has brought the indoor airborne transmission issue to the forefront. Although ventilation systems provide clean air and dilute indoor contaminated air, there is strong evidence that airborne transmission is the main route for contamination spread. This review paper aims to critically investigate ventilation impacts on particle spread and identify efficient ventilation strategies in controlling aerosol distribution in clinical and non-clinical environments. This article also examines influential ventilation design features (i.e., exhaust location) affecting ventilation performance in preventing aerosols spread. This paper shortlisted published documents for a review based on identification (keywords), pre-processing, screening, and eligibility of these articles. The literature review emphasizes the importance of ventilation systems' design and demonstrates all strategies (i.e., mechanical ventilation) could efficiently remove particles if appropriately designed. The study highlights the need for occupant-based ventilation systems, such as personalized ventilation instead of central systems, to reduce cross-infections. The literature underlines critical impacts of design features like ventilation rates and the number and location of exhausts and suggests designing systems considering airborne transmission. This review underpins that a higher ventilation rate should not be regarded as a sole indicator for designing ventilation systems because it cannot guarantee reducing risks. Using filtration and decontamination devices based on building functionalities and particle sizes can also increase ventilation performance. This paper suggests future research on optimizing ventilation systems, particularly in high infection risk spaces such as multi-storey hotel quarantine facilities. This review contributes to adjusting ventilation facilities to control indoor aerosol transmission.

The influence of mask use on the spread of COVID-19 during pandemic in New York City

In New York City, the situation of COVID-19 is so serious that it has caused hundreds of thousands of people to be infected due to its strong infectivity. The desired effect of wearing masks by the public is not ideal, though increasingly recommended by the WHO. In order to reveal the potential effect of mask use, we posed a dynamical model with the effective coverage of wearing face masks to assess the impact of mask use on the COVID-19 transmission. We obtained the basic reproduction number  R 0 which determined the global dynamics. According to the implement of policies in New York City, we divided the transmission of COVID-19 in three stages. Based on mathematical model and data, we obtain the mean value  R 0 = 1 . 822 in the first stage of New York City, while  R 0 = 0 . 6483 in the second stage due to that the US Centers for Disease Control and Prevention (CDC) recommended the public wear masks on April 3, 2020,  R 0 = 1 . 024 in the third stage after reopening. It was found that if the effective coverage rate of mask use  α exceed a certain value  α c = 0 . 182 , COVID-19 can be well controlled in the second stage of New York City. Additionally, when the effective coverage of masks reaches a certain level  α = 0 . 5 , the benefits are not obvious with the increased coverage rate compared to the cost of medical resources. Moreover, if the effective coverage of mask use in public reaches 20% in the first stage, then the cumulative confirmed cases will be reduced about 50% by 03 April, 2020. Our results demonstrated a new insight on the effect of mask use in controlling the transmission of COVID-19.

The impact of heating, ventilation, and air conditioning design features on the transmission of viruses, including the 2019 novel coronavirus: A systematic review of ventilation and coronavirus

Aerosol transmission has been a pathway for the spread of many viruses. Similarly, emerging evidence has determined aerosol transmission for Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) and the resulting COVID-19 pandemic to be significant. As such, data regarding the effect of Heating, Ventilation, and Air Conditioning (HVAC) features to control and mitigate virus transmission is essential. A systematic review was conducted to identify and comprehensively synthesize research examining the effectiveness of ventilation for mitigating transmission of coronaviruses. A comprehensive search was conducted in Ovid MEDLINE, Compendex, Web of Science Core to January 2021. Study selection, data extraction, and risk of bias assessments were performed by two authors. Evidence tables were developed and results were described narratively. Results from 32 relevant studies showed that: increased ventilation rate was associated with decreased transmission, transmission probability/risk, infection probability/risk, droplet persistence, virus concentration, and increased virus removal and virus particle removal efficiency; increased ventilation rate decreased risk at longer exposure times; some ventilation was better than no ventilation; airflow patterns affected transmission; ventilation feature (e.g., supply/exhaust, fans) placement influenced particle distribution. Few studies provided specific quantitative ventilation parameters suggesting a significant gap in current research. Adapting HVAC ventilation systems to mitigate virus transmission is not a one-solution-fits-all approach. Changing ventilation rate or using mixing ventilation is not always the only way to mitigate and control viruses. Practitioners need to consider occupancy, ventilation feature (supply/exhaust and fans) placement, and exposure time in conjunction with both ventilation rates and airflow patterns. Some recommendations based on quantitative data were made for specific scenarios (e.g., using air change rate of 9 h-1 for a hospital ward). Other recommendations included using or increasing ventilation, introducing fresh air, using maximum supply rates, avoiding poorly ventilated spaces, assessing fan placement and potentially increasing ventilation locations, and employing ventilation testing and air balancing checks. Trial registration: PROSPERO 2020 CRD42020193968.

Transmission of SARS-CoV-2 during air travel: a descriptive and modelling study

OBJECTIVES

To explore the potential of SARS-CoV-2 spread during air travel and the risk of in-flight transmission.

METHODS

We enrolled all passengers and crew suspected of being infected with SARS-CoV-2, who bounded for Beijing on international flights. We specified the characteristics of all confirmed cases of COVID-19 infection and utilised Wells-Riley equation to estimate the infectivity of COVID-19 during air travel.

RESULTS

We screened 4492 passengers and crew with suspected COVID-19 infection, verified 161 confirmed cases (mean age 28.6 years), and traced two confirmed cases who may have been infected in the aircraft. The estimated infectivity was 375 quanta/h (range 274-476), while the effective infectivity was only 4 quanta/h (range 2-5). The risk of per-person infection during a 13 h air travel in economy class was 0.56‰ (95% CI 0.41‰-0.72‰).

CONCLUSION

We found that the universal use of face masks on the flight, together with the plane's ventilation system, significantly decreased the infectivity of COVID-19.KEY MESSAGESThe COVID-19 pandemic is changing the lifestyle in the world, especially air travel which has the potential to spread SARS-CoV-2.The universal use of face masks on the flight, together with the plane's ventilation system, significantly decreased the infectivity of COVID-19 on an aircraft.Our findings suggest that the risk of infection in aircraft was negligible.

Survey of air exchange rates and evaluation of airborne infection risk of COVID-19 on commuter trains

To identify potential countermeasures for coronavirus disease (COVID-19), we determined the air exchange rates in stationary and moving train cars under various conditions in July, August, and December 2020 in Japan. When the doors were closed, the air exchange rates in both stationary and moving trains increased with increasing area of window-opening (0.23-0.78/h at 0 m2, windows closed to 2.1-10/h at 2.86 m2, fully open). The air exchange rates were one order of magnitude higher when doors were open than when closed. With doors closed, the air exchange rates were higher when the centralized air conditioning (AC) and crossflow fan systems (fan) were on than when off. The air exchange rates in moving trains increased as train speed increased, from 10/h at 20 km/h to 42/h at 57 km/h. Air exchange rates did not differ significantly between empty cars and those filled with 230 mannequins representing commuters. The air exchange rates were lower during aboveground operation than during underground. Assuming that 30-300 passengers travel in a train car for 7-60 min and that the community infection rate is 0.0050-0.30%, we estimated that commuters' infection risk on trains was reduced by 91-94% when all 12 windows were opened (to a height of 10 cm) and the AC/fan was on compared with that when windows were closed and the AC/fan was off.

Predicting COVID-19 Transmission to Inform the Management of Mass Events: Model-Based Approach

BACKGROUND

Modelling COVID-19 transmission at live events and public gatherings is essential to controlling the probability of subsequent outbreaks and communicating to participants their personalized risk. Yet, despite the fast-growing body of literature on COVID-19 transmission dynamics, current risk models either neglect contextual information including vaccination rates or disease prevalence or do not attempt to quantitatively model transmission.

OBJECTIVE

This paper attempted to bridge this gap by providing informative risk metrics for live public events, along with a measure of their uncertainty.

METHODS

Building upon existing models, our approach ties together 3 main components: (1) reliable modelling of the number of infectious cases at the time of the event, (2) evaluation of the efficiency of pre-event screening, and (3) modelling of the event's transmission dynamics and their uncertainty using Monte Carlo simulations.

RESULTS

We illustrated the application of our pipeline for a concert at the Royal Albert Hall and highlighted the risk's dependency on factors such as prevalence, mask wearing, and event duration. We demonstrate how this event held on 3 different dates (August 20, 2020; January 20, 2021; and March 20, 2021) would likely lead to transmission events that are similar to community transmission rates (0.06 vs 0.07, 2.38 vs 2.39, and 0.67 vs 0.60, respectively). However, differences between event and background transmissions substantially widened in the upper tails of the distribution of the number of infections (as denoted by their respective 99th quantiles: 1 vs 1, 19 vs 8, and 6 vs 3, respectively, for our 3 dates), further demonstrating that sole reliance on vaccination and antigen testing to gain entry would likely significantly underestimate the tail risk of the event.

CONCLUSIONS

Despite the unknowns surrounding COVID-19 transmission, our estimation pipeline opens the discussion on contextualized risk assessment by combining the best tools at hand to assess the order of magnitude of the risk. Our model can be applied to any future event and is presented in a user-friendly RShiny interface. Finally, we discussed our model's limitations as well as avenues for model evaluation and improvement.

Correlation of Respiratory Aerosols and Metabolic Carbon Dioxide

Respiratory aerosols from breathing and talking are an important transmission route for viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Previous studies have found that particles with diameters ranging from 10 nm to 145 μm are produced from different regions in the respiratory system and especially smaller particles can remain airborne for long periods while carrying viral RNA. We present the first study in which respiratory aerosols have been simultaneously measured with carbon dioxide (CO2) to establish the correlation between the two concentrations. CO2 concentrations are easily available through low-cost sensors and could be used to estimate viral exposure through this correlation, whereas source-specific aerosol measurements are complicated and not possible with low-cost sensors. The increase in both respiratory aerosols and CO2 was linear over ten minutes in a 2 m3 chamber for all participants, suggesting a strong correlation. On average, talking released more particles than breathing, with 14,600 ± 16,800 min−1 (one-σ standard deviation) and 6210 ± 5630 min−1 on average, respectively, while CO2 increased with 139 ± 33 ppm min−1 during talking and 143 ± 29 ppm min−1 during breathing. Assuming a typical viral load of 7×106 RNA copies per mL of oral fluid, ten minutes of talking and breathing are estimated to produce 1 and 16 suspended RNA copies, respectively, correlating to a CO2 concentration of around 1800 ppm in a 2 m3 chamber. However, viral loads can vary by several orders of magnitude depending on the stage of the disease and the individual. It was therefore concluded that, by measuring CO2 concentrations, only the number and volume concentrations of released particles can be estimated with reasonable certainty, while the number of suspended RNA copies cannot.

Environmental Surveillance and Transmission Risk Assessments for SARS-CoV-2 in a Fitness Center

Fitness centers are considered high risk for SARS-CoV-2 transmission due to their high human occupancy and the type of activity taking place in them, especially when individuals pre-symptomatic or asymptomatic for COVID-19 exercise in the facilities. In this study, air (N=21) and surface (N=8) samples were collected at a fitness center through five sampling events from August to November 2020 after the reopening restrictions were lifted in Florida. The total attendance was ~2500 patrons during our air and environmental sampling work. Air samples were collected using stationary and personal bioaerosol samplers. Moistened flocked nylon swabs were used to collect samples from high-touch surfaces. We did not detect SARS-CoV-2 by rRT-PCR analyses in any air or surface sample. A simplified infection risk model based on the Wells-Riley equation predicts that the probability of infection in this fitness center was 1.77% following its ventilation system upgrades based on CDC guidelines, and that risk was further reduced to 0.89% when patrons used face masks. Our model also predicts that a combination of high ventilation, minimal air recirculation, air filtration, and UV sterilization of recirculated air reduced the infection risk up to 94% compared to poorly ventilated facilities. Amongst these measures, high ventilation with outdoor air is most critical in reducing the airborne transmission of SARS-CoV-2. For buildings that cannot avoid air recirculation due to energy costs, the use of high filtration and/or air disinfection devices are alternatives to reducing the probability of acquiring SARS-CoV-2 through inhalation exposure. In contrast to the perceived ranking of high risk, the infection risk in fitness centers that follow CDC reopening guidance, including implementation of engineering and administrative controls, and use of personal protective equipment, can be low, and these facilities can offer a relatively safe venue for patrons to exercise.

Simulating near-field enhancement in transmission of airborne viruses with a quadrature-based model

Some infectious diseases, such as influenza, tuberculosis, and SARS-CoV-2, may be transmitted when virus-laden particles expelled from an infectious person are inhaled by someone else, which is known as the airborne transmission route. These virus-laden particles are more concentrated in the expiratory jet of an infectious person than elsewhere in a well-mixed room, but this near-field enhancement in virion exposure has not been well quantified. Transmission of airborne viruses depends on factors that are inherently variable and, in many cases, poorly constrained, and quantifying this uncertainty requires large ensembles of model simulations that span the variability in input parameters. However, models that are well-suited to simulate the near-field evolution of respiratory particles are also computationally expensive, which limits the exploration of parametric uncertainty. In order to perform many simulations that span the wide variability in factors governing airborne transmission, we developed the Quadrature-based model of Respiratory Aerosol and Droplets (QuaRAD). QuaRAD is an efficient framework for simulating the evolution of virus-laden particles after they are expelled from an infectious person, their deposition to the nasal cavity of a susceptible person, and the subsequent risk of initial infection. We simulated 10 000 scenarios to quantify the risk of initial infection by a particular virus, SARS-CoV-2. The predicted risk of infection was highly variable among scenarios and, in each scenario, was strongly enhanced near the infectious individual. In more than 50% of scenarios, the physical distancing needed to avoid near-field enhancements in airborne transmission was beyond the recommended safe distance of two meters (six feet) if the infectious person is not wearing a mask, though this distance defining the near-field extent was also highly variable among scenarios; the variability in the near-field extent is explained predominantly by variability in expiration velocity. Our findings suggest that maintaining at least two meters of distance from an infectious person greatly reduces exposure to airborne virions; protections against airborne transmission, such as N95 respirators, should be available when distancing is not possible.

A systematic approach to estimating the effectiveness of multi-scale IAQ strategies for reducing the risk of airborne infection of SARS-CoV-2

The unprecedented coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has made more than 125 million people infected and more than 2.7 million people dead globally. Airborne transmission has been recognized as one of the major transmission routes for SARS-CoV-2. This paper presents a systematic approach for evaluating the effectiveness of multi-scale IAQ control strategies in mitigating the infection risk in different scenarios. The IAQ control strategies across multiple scales from a whole building to rooms, and to cubical and personal microenvironments and breathing zone, are introduced, including elevated outdoor airflow rates, high-efficiency filters, advanced air distribution strategies, standalone air cleaning technologies, personal ventilation and face masks. The effectiveness of these strategies for reducing the risk of COVID-19 infection are evaluated for specific indoor spaces, including long-term care facility, school and college, meat plant, retail stores, hospital, office, correctional facility, hotel, restaurant, casino and transportation spaces like airplane, cruise ship, subway, bus and taxi, where airborne transmission are more likely to occur due to high occupancy densities. The baseline cases of these spaces are established according to the existing standards, guidelines or practices. Several integrated mitigation strategies are recommended and classified based on their relative cost and effort of implementation for each indoor space. They can be applied to help meet the current challenge of ongoing COVID-19, and provide better preparation for other possible epidemics and pandemics of airborne infectious diseases in the future.

Ventilation Assessment by Carbon Dioxide Levels in Dental Treatment Rooms

It is important for dental care professionals to reliably assess carbon dioxide (CO₂) levels and ventilation rates in their offices in the era of frequent infectious disease pandemics. This study was to evaluate CO₂ levels in dental operatories and determine the accuracy of using CO₂ levels to assess ventilation rate in dental clinics. Mechanical ventilation rate in air change per hour (ACH_VENT) was measured with an air velocity sensor and airflow balancing hood. CO₂ levels were measured in these rooms to analyze factors that contributed to CO₂ accumulation. Ventilation rates were estimated using natural steady-state CO₂ levels during dental treatments and experimental CO₂ concentration decays by dry ice or mixing baking soda and vinegar. We compared the differences and assessed the correlations between ACH_VENT and ventilation rates estimated by the steady-state CO₂ model with low (0.3 L/min, ACH_SS30) or high (0.46 L/min, ACH_SS46) CO₂ generation rates, by CO₂ decay constants using dry ice (ACH_DI) or baking soda (ACH_BV), and by time needed to remove 63% of excess CO₂ generated by dry ice (ACH_DI63%) or baking soda (ACH_BV63%). We found that ACH_VENT varied from 3.9 to 35.0 in dental operatories. CO₂ accumulation occurred in rooms with low ventilation (ACH_VENT ≤6) and overcrowding but not in those with higher ventilation. ACH_SS30 and ACH_SS46 correlated well with ACH_VENT (r = 0.83, P = 0.003), but ACH_SS30 was more accurate for rooms with low ACH_VENT. Ventilation rates could be reliably estimated using CO₂ released from dry ice or baking soda. ACH_VENT was highly correlated with ACH_DI (r = 0.99), ACH_BV (r = 0.98), ACH_DI63% (r = 0.98), and ACH_BV63% (r = 0.98). There were no statistically significant differences between ACH_VENT and ACH_DI63% or ACH_BV63%. We conclude that ventilation rates could be conveniently and accurately assessed by observing the changes in CO₂ levels after a simple mixing of household baking soda and vinegar in dental settings.

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.

Ten questions concerning occupant health in buildings during normal operations and extreme events including the COVID-19 pandemic

Even before the COVID-19 pandemic, people spent on average around 90% of their time indoors. Now more than ever, with work-from-home orders in place, it is crucial that we radically rethink the design and operation of buildings. Indoor Environmental Quality (IEQ) directly affects the comfort and well-being of occupants. When IEQ is compromised, occupants are at increased risk for many diseases that are exacerbated by both social and economic forces. In the U.S. alone, the annual cost attributed to sick building syndrome in commercial workplaces is estimated to be between $10 billion to $70 billion. It is imperative to understand how parameters that drive IEQ can be designed properly and how buildings can be operated to provide ideal IEQ to safeguard health. While IEQ is a fertile area of scholarship, there is a pressing need for a systematic understanding of how IEQ factors impact occupant health. During extreme events, such as a global pandemic, designers, facility managers, and occupants need pragmatic guidance on reducing health risks in buildings. This paper answers ten questions that explore the effects of buildings on the health of occupants. The study establishes a foundation for future work and provides insights for new research directions and discoveries.