Airborne Infectious Disease Transmission Research Articles

Modelling the transmission and control of airborne infectious disease in healthcare settings

The transmission of airborne infectious diseases, such as tuberculosis (TB) and coronavirus disease 2019 (COVID-19), among healthcare workers (HCW) in healthcare settings (HCS), remains a public health concern. TB and COVID-19 transmission mostly occur in congregated and confined areas with limited ventilation per person through respiratory droplets from infectious individuals.

Meta-Aerogel Electric Trap Enables Instant and Continuable Pathogen Killing in Face Masks.

The tremendous menace of the COVID-19 pandemic has underscored the urgency for antipathogen masks to stop the transmission of airborne infectious diseases. Most prevailing antipathogen masks manifest a slower sterilization rate that lags behind the pathogen momentum traversing the masks, thereby engendering an elevated susceptibility to infection. Here we tailor nanofibrous meta-aerogel electric traps, 3D-assembled from self-knotted carbon nanotube networks in an all rigid nanofibrous skeleton. This superior configuration revolves around the creation of numerous "dielectrophoretic-aerodynamic grippers", which are capable of directional manipulation of microbes toward the region of the lethal intensive electric field. Based on this, we present a disinfection unit comprising a pair of aerogel electrodes that demonstrate a rapid killing rate (>99.99% biocidal efficacy within 0.016 s) and long-term durability (12 h of continuous operation). Additionally, a microbutton lithium cell is employed as a power supply to fabricate an antipathogen face mask with this disinfection unit, which exhibits superior pathogen inactivation efficacy compared to commercial masks. This scalable biocidal protective equipment holds great potential for use in emergency medical services.

Developing a survival probability-based Lagrangian model for predicting ultraviolet disinfection of bioaerosols in enclosed environments

The transmission of airborne infectious diseases in enclosed environments has become a significant public health issue. Far-ultraviolet C (UVC) lights can be used safely and effectively to disinfect bioaerosols and reduce the risk of airborne infectious disease transmission. To ensure proper use of far-UVC systems, an improved Lagrangian method for predicting the dispersion, deposition, and far-UVC disinfection of bioaerosols was proposed. First, an improved Lagrangian model considering the probability of bioaerosol survival was developed for predicting the UVC disinfection of airborne bioaerosols in enclosed environments. The UVC disinfection of surfaces with deposited bioaerosols was implemented into the deposition module of the Lagrangian model by introducing the concept of equivalent deposition number. Experimental data on far-UVC disinfection of E. Coli in the air and on the surfaces in a ventilated chamber were used to validate the proposed model. The validation results show that the proposed model can predict the bioaerosol dispersion, deposition, and far-UVC disinfection reasonably well. The validated model was then employed to calculate the far-UVC disinfection of airborne and surface SARS-CoV-2 bioaerosols in a Mass Transit Railway (MTR) train compartment in Hong Kong. According to the calculation results, the far-UVC lamps are effective in reducing the passengers’ exposure to SARS-CoV-2 bioaerosols.

Possible high COVID-19 airborne infection risk in deep and poorly ventilated 2D street canyons

AbstractDespite the widespread assumption that outdoor environments provide sufficient ventilation and dilution capacity to mitigate the risk of COVID-19 infection, there is little understanding of airborne infection risk in outdoor urban areas with poor ventilation. To address this gap, we propose a modified Wells-Riley model based on the purging flow rate (QPFR), by using computational fluid dynamics (CFD) simulations. The model quantifies the outdoor risk in 2D street canyons with different approaching wind speeds, urban heating patterns and aspect ratios (building height to street width). We show that urban morphology plays a critical role in controlling airborne infectious disease transmission in outdoor environments, especially under calm winds; with deep street canyons (aspect ratio > 3) having a similar infection risk as typical indoor environments. While ground and leeward wall heating could reduce the risk, windward heating (e.g., windward wall ~10 K warmer than the ambient air) can increase the infection risk by up to 75%. Our research highlights the importance of considering outdoor infection risk and the critical role of urban morphology in mitigating airborne infection risk. By identifying and addressing these risks, we can inform measures that may enhance public health and safety, particularly in densely populated urban environments.

Assessment of ventilation in low-resource healthcare settings: Montserrado County, Liberia—2022−2023

Background: Mitigating the risk of nosocomial respiratory disease transmission in the healthcare facilities of low- and middle−income countries (LMICs) poses unique challenges because mechanical ventilation and mixed−mode strategies are often unavailable. Carbon dioxide (CO2) can serve as a proxy for ventilation and, hence, airborne infectious disease transmission risk in naturally ventilated spaces. We assessed the adequacy of ventilation in Liberian hospitals. Methods: We sampled 3 hospitals, both urban and rural, in Montserrado County, Liberia. Moreover, 3 CO2 meters were concurrently utilized to measure CO2 levels at a 1-meter height in every patient-care room in each facility. We recorded temperature, humidity, room dimensions, and number of people in the rooms. From these variables, we calculated absolute ventilation using the ASHRAE equation to determine areas with the highest risk of nosocomial respiratory disease transmission. We also recorded qualitative observations about the sampled spaces. Results: From August 2022 to February 2023, 39 rooms in 3 healthcare facilities were sampled. Initial quantitative findings show that only 8 rooms (21%) met the WHO-recommended ventilation rate of 60 L per second per person. The average ventilation rate per person in the adequately ventilated settings was 86 L per second per patient, compared to 19 liters per second per patient in inadequately ventilated rooms. Additionally, 467 ppm mean CO2 was noted in well-ventilated rooms compared to 895 ppm mean CO2 in inadequately ventilated rooms.Initial qualitative observations showed that facilities with lower CO2 readings tended to be older constructions that likely had been constructed with airborne disease such as tuberculosis in mind. Willingness to open windows was limited by lack of window screens for malaria prevention, and there was a pervasive fallacy that air conditioning was a source of ventilation. Correspondingly, of the 31 inadequately ventilated rooms, 22 (71%) had operating air conditioning units compared with 4 (50%) of the 8 adequately ventilated rooms. Overall, of the 13 rooms without air conditioning, 7 (54%) were more frequently characterized by open windows compared to only 5 of 26 (28%) of rooms that did have air conditioners. Conclusions: Being prepared for the next respiratory disease outbreak and creating more resilient healthcare systems in LMICs requires a frameshift of prevention strategies. Measuring CO2 provides a simple strategy for identifying areas at highest risk for nosocomial respiratory disease transmission, which can be prioritized for low-cost environmental interventions, such as provision of window screens, as part of routine infection prevention and control efforts.Disclosure: None

Experimental investigation on the purification performance of particle and planktonic bacteria in the human body micro-environment using low-temperature plasma

Airborne infectious disease transmission in the built environment has caused casualty to people's life. To minimize the inhalation risk of bioaerosol in the human body micro-environment, a wearable low-temperature plasma (LTP) device was developed. The gas fractions produced by the device were studied by the optical emission spectroscopy. The sterilization performance on E. coli and S. albus at different treatment times was investigated. Meanwhile, the purification efficiency of particle and planktonic bacteria in a confined indoor space was also investigated by combining the wearable device with a thermal manikin. Results demonstrated that N2(B3Пg→A3Σu+) and ·OH were the main active species. The concentration of E. coli and S. albus could be reduced from 0.05 to 0.92 log units after treatment by LTP sterilized species. Besides, the particle removal efficiency of LTP on the thermal manikin ranges from 12.55% to 36.37%. By combination of the LTP device and the indoor air cleaners (ACs), the particle cleaning efficiency in the breathing zone of people can be significantly improved. Compared with the natural settlement scenario, the purification efficiency of the planktonic bacteria by the LTP device could reach 24.96%. This study shows that LTP technology can be used as a complementary tool to the current HVAC technology for protection of occupant's breathing air in the human body micro-environment.

A novel VOC breath tracer method to evaluate indoor respiratory exposures in the near- and far-fields; implications for the spread of respiratory viruses

BackgroundSeveral studies suggest that far-field transmission (>6 ft) explains a significant number of COVID-19 superspreading outbreaks.ObjectiveTherefore, quantifying the ratio of near- and far-field exposure to emissions from a source is key to better understanding human-to-human airborne infectious disease transmission and associated risks.MethodsIn this study, we used an environmentally-controlled chamber to measure volatile organic compounds (VOCs) released from a healthy participant who consumed breath mints, which contained unique tracer compounds. Tracer measurements were made at 0.76 m (2.5 ft), 1.52 m (5 ft), 2.28 m (7.5 ft) from the participant, as well as in the exhaust plenum of the chamber.ResultsWe observed that 0.76 m (2.5 ft) trials had ~36–44% higher concentrations than other distances during the first 20 minutes of experiments, highlighting the importance of the near-field exposure relative to the far-field before virus-laden respiratory aerosol plumes are continuously mixed into the far-field. However, for the conditions studied, the concentrations of human-sourced tracers after 20 minutes and approaching the end of the 60-minute trials at 0.76 m, 1.52 m, and 2.28 m were only ~18%, ~11%, and ~7.5% higher than volume-averaged concentrations, respectively.SignificanceThis study suggests that for rooms with similar airflow parameters disease transmission risk is dominated by near-field exposures for shorter event durations (e.g., initial 20–25-minutes of event) whereas far-field exposures are critical throughout the entire event and are increasingly more important for longer event durations.Impact statementWe offer a novel methodology for studying the fate and transport of airborne bioaerosols in indoor spaces using VOCs as unique proxies for bioaerosols. We provide evidence that real-time measurement of VOCs can be applied in settings with human subjects to estimate the concentration of bioaerosol at different distances from the emitter. We also improve upon the conventional assumption that a well-mixed room exhibits instantaneous and perfect mixing by addressing spatial distances and mixing over time. We quantitatively assessed the exposure levels to breath tracers at alternate distances and provided more insights into the changes on “near-field to far-field” ratios over time. This method can be used in future to estimate the benefits of alternate environmental conditions and occupant behaviors.

Predicting spatial distribution of ultraviolet irradiance and disinfection of exhaled bioaerosols with a modified irradiance model

The transmission of airborne infectious diseases in indoor environments has become a major public health concern. Ultraviolet C lights are effective in inactivating bioaerosols to reduce infection risks. To facilitate the design and application of UVC systems, this study developed a modified irradiance model for calculating the spatial irradiance distribution when unstructured meshes are used for arbitrary reflective surfaces. With the modified irradiance model, the computational fluid dynamics (CFD)-Eulerian model was used to predict the dispersion and UV disinfection of bioaerosols. The proposed model was first preliminarily validated using measured data for in-duct ultraviolet germicidal lamps from the literature. For further validation of the proposed model in a relatively complex environment, experimental measurements of the detailed spatial irradiance distribution and bioaerosol concentration exhaled from a manikin in a ventilated chamber with a far UVC lamp were compared with calculated results. It was found that the proposed modified irradiance model can predict the spatial irradiance distribution reasonably well when unstructured meshes are used for arbitrary reflective surfaces. Furthermore, the modified irradiance model with the CFD-Eulerian model can predict the dispersion and UV disinfection of exhaled bioaerosols in indoor environments reasonably well. Finally, the validated model was used to predict person-to-person influenza A virus transport in a room with a ventilation rate of 3 ACH and a far UVC lamp with an effective output power of 0.34 W. The results show that the far UVC lamp can effectively reduce the receptor's exposure to influenza A virus by 65%.

Development and application of an indoor carbon dioxide metric.

Indoor carbon dioxide (CO2 ) concentrations have been considered for decades in evaluating indoor air quality (IAQ) and ventilation, and more recently in discussions of the risk of airborne infectious disease transmission. However, many of these applications reflect a lack of understanding of the connection between indoor CO2 levels, ventilation, and IAQ. For example, a single indoor concentration such as 1000ppmv is often used as a metric of IAQ and ventilation without an understanding of the significance of this or any other value. CO2 concentrations are of limited value as IAQ metrics, and a single concentration will not serve as a ventilation indicator for spaces with different occupancies and ventilation requirements. An approach has been developed to estimate a space-specific CO2 level that can serve as a metric of outdoor ventilation rates. The concept is to estimate the CO2 concentration that would be expected in a specific space given its intended or expected ventilation rate, the number of occupants, the rate at which they generate CO2 , and the time that has transpired since the space was occupied. This paper describes the approach and presents example calculations for several commercial, institutional, and residential occupancies.

Modeling disease transmission in a train carriage using a simple 1D-model.

Understanding airborne infectious disease transmission on public transport is essential to reducing the risk of infection of passengers and crew members. We propose a new one-dimensional (1D) model that predicts the longitudinal dispersion of airborne contaminants and the risk of disease transmission inside a railway carriage. We compare the results of this 1D-model to the predictions of a model that assumes the carriage is fully mixed. The 1D-model is validated using measurements of controlled carbon-dioxide experiments conducted in a full-scale railway carriage. We use our results to provide novel insights into the impact of various strategies to reduce the risk of airborne transmission on public transport.

Recent progress on studies of airborne infectious disease transmission, air quality, and thermal comfort in the airliner cabin air environment.

Airborne transmission of infectious diseases through air travel has become a major concern, especially during the COVID‐19 pandemic. The flying public and crew members have long demanded better air quality and thermal comfort in commercial airliner cabins. This paper reviewed studies related to the airliner cabin air environment that have been published in scientific journals since 2000, to understand the state‐of‐the‐art in cabin air environment design and the efforts made to improve this environment. In this critical review, this paper discusses the challenges and opportunities in studying the cabin air environment. The literature review concluded that current environmental control systems for airliner cabins have done little to stop the airborne transmission of infectious diseases. There were no reports of significant air quality problems in cabins, although passengers and crew members have complained of some health‐related issues. The air temperature in cabins needs to be better controlled, and therefore, better thermal comfort models for airliners should be developed. Low humidity is a major complaint from passengers and crew members. Gaspers are used by passengers to adjust thermal comfort, but they do not improve air quality. Various personalized and displacement ventilation systems have been developed to improve air quality and thermal comfort. Air cleaning technologies need to be further developed. Good tools are available for designing a better cabin air environment.

Personalized Ventilation as a Possible Strategy for Reducing Airborne Infectious Disease Transmission on Commercial Aircraft

In the last decade, there has been an increase in ease and affordability of air travel in terms of mobility for people all around the world. Airplane passengers may experience different risks of contracting airborne infectious diseases onboard aircraft, such as influenza or severe acute respiratory syndrome (SARS-CoV-1 and SARS-CoV-2), due to nonuniform airflow patterns inside the airplane cabin or proximity to an infected person. In this paper, a novel approach for reducing the risk of contracting airborne infectious diseases is presented that uses a low-momentum personalized ventilation system with a protective role against airborne pathogens. Numerical simulations, supported by nonintrusive experimental measurements for validation purposes, were used to demonstrate the effectiveness of the proposed system. Simulation and experimental results of the low-momentum personalized ventilation system showed the formation of a microclimate around each passenger with cleaner and fresher air than produced by the general mixing ventilation systems.

Passenger-to-Car Assignment Optimization Model for High-Speed Railway with Risk of COVID-19 Transmission Consideration

Narrow and closed spaces like high-speed train cabins are at great risk for airborne infectious disease transmission. With the threat of COVID-19 as well as other potential contagious diseases, it is necessary to protect passengers from infection. Except for the traditional preventions such as increasing ventilation or wearing masks, this paper proposes a novel measurement that optimizes passenger-to-car assignment schemes to reduce the infection risk for high-speed railway passengers. First, we estimated the probability of an infected person boarding the train at any station. Once infectors occur, the non-steady-state Wells–Riley equation is used to model the airborne transmission intercar cabin. The expected number of susceptible passengers infected on the train can be calculated, which is the so-called overall infection risk. The model to minimize overall infection risk, as a pure integer quadratic programming problem, is solved by LINGO software and tested on several scenarios compared with the classical sequential and discrete assignment strategies used in China. The results show that the proposed model can reduce 67.6% and 56.8% of the infection risk in the base case compared to the sequential and discrete assignment, respectively. In other scenarios, the reduction lies mostly between 10% and 90%. The optimized assignment scheme suggests that the cotravel itinerary among passengers from high-risk and low-risk areas should be reduced, as well as passengers with long- and short-distance trips. Sensitivity analysis shows that our model works better when the incidence is higher at downstream or low-flow stations. Increasing the number of cars and car service capacity can also improve the optimization effect. Moreover, the model is applicable to other epidemics since it is insensitive to the Wells–Riley equation parameters. The results can provide a guideline for railway operators during the post-COVID-19 and other epidemic periods.

An improved Markov chain model with modified turbulence diffusion for predicting indoor particle transport

Correctly predicting indoor particle transport is crucial for the design of air distribution to reduce the transmission of airborne infectious diseases. In recent years, a model for predicting particle transport based on the Markov chain technique has emerged, with the advantage of fast computing speed. However, the turbulence diffusion modeling approach in this Markov chain model is semi-empirical without justification. The present study aims to develop an improved Markov chain model with modified turbulence diffusion to increase its accuracy in predicting indoor particle transport. The proposed Markov chain model with modified turbulence diffusion was first validated with experimental data on transient particle transport under steady airflow from the literature. In addition, laboratory experiments on transient particle transport under unsteady periodic ventilation, which are rarely found in the literature, were conducted to further validate the improved Markov chain model. The results show that the improved Markov chain model can correctly predict transient particle transport under both steady and unsteady airflow in comparison with the experimental data. In addition, the improved Markov chain model was more accurate than the existing model in predicting transient particle transport, especially under unsteady airflow with periodic ventilation. By improving the turbulence diffusion modeling, the normalized root-mean-square deviation values of the Markov chain model decreased from 0.115/0.084 to 0.108/0.064 for the two cases in this study.

HVAC system requirements for protection against epidemics similar to Covid-19

Tuberculosis and in some cases, flu, colds and other airborne diseases. Since research is one of the biggest concerns of causing influenza pandemics, most research surrounding aerosol contamination revolves around environmental influences on the influenza virus. Many literatures suggest that influenza is transmitted primarily through close contact, such as exposure to large respiratory droplets, direct mouth-to-mouth contact and short-term exposure to infectious aerosols. Diffusion can be accelerated or controlled by heating, ventilation and air conditioning (HVAC) systems. Researches continue that advances state of knowledge in the specific techniques that control airborne infectious disease transmission through HVAC systems, including ventilation rates, airflow regimes, filtration, and ultraviolet germicidal irradiation (UVGI). In this paper three methods of transmission of Airborne Infectious Diseases are discussed, namely through direct contact, large droplet contact, inhalation of droplet core. An extensive literature review of many papers was conducted infectious diseases spread in several different ways and the transmission of infectious viruses. This review targets direct and indirect contact as well as infectious viruses known to be transmitted from the air. And he focused on preventive ventilation systems for these targets. This paper will give idea to support further research on engineering controls to reduce infectious disease transmission.

Minimizing the respiratory pathogen transmission: Numerical study and multi-objective optimization of ventilation systems in a classroom

Schools are recognized as high-risk spaces in airborne infectious disease transmission due to occupant density and activity level. Therefore, it is critical to conduct studies and provide proper solutions regarding the spread of airborne transmission diseases to the lowest possible in schools. In this study, the performance of five various ventilation systems regarding control the spread of airborne particles in a classroom were studied by Computational Fluid Dynamics (CFD), and then, the best case was selected with regard to the least probability of infection spread. These cases with various locations of inlet and outlet vents are considered, and the spread of particles is studied. A multi-objective optimization process is then performed to understand the effects of design variables, including air inlet width, air change per hour (ACH), and inlet air temperature on the thermal comfort conditions according to suggested standard values and relations for calculating each of these parameters based on the design variables are proposed. Desirability functions are used to determine the range of variables that result in thermally comfortable conditions and maximum desirability of 0.952 with a width of 0.130 m, temperature of 296.60 K, and value of ACH between 9.689 and 9.858 results is obtained.

Regional Relative Risk, a Physics-Based Metric for Characterizing Airborne Infectious Disease Transmission.

Airborne infectious disease transmission events occur over a wide range of spatial scales and can be an important means of disease transmission. Physics- and biology-based models can assist in predicting airborne transmission events, overall disease incidence, and disease control strategy efficacy. We describe a new theory that extends current approaches for the case in which an individual is infected by a single airborne particle, including the scenario in which numerous infectious particles are present in the air but only one causes infection. A single infectious particle can contain more than one pathogenic microorganism and be physically larger than the pathogen itself. This approach allows robust relative risk estimates even when there is wide variation in (i) individual exposures and (ii) the individual response to that exposure (the pathogen dose-response function can take any mathematical form and vary by individual). Based on this theory, we propose the regional relative risk-a new metric, distinct from the traditional relative risk metric, that compares the risk between two regions. In theory, these regions can range from individual rooms to large geographic areas. In this paper, we apply the regional relative risk metric to outdoor disease transmission events over spatial scales ranging from 50 m to 20 km, demonstrating that in many common cases minimal input information is required to use the metric. Also, we demonstrate that the model predictions are consistent with data from prior outbreaks. Future efforts could apply and validate this theory for other spatial scales, such as transmission within indoor environments. This work provides context for (i) the initial stages of an airborne disease outbreak and (ii) larger-scale disease spread, including unexpected low-probability disease "sparks" that potentially affect remote populations, a key practical issue in controlling airborne disease outbreaks. IMPORTANCE Airborne infectious disease transmission events occur over a wide range of spatial scales and can be important to disease outbreaks. We describe a new physics- and biology-based theory for the important case in which individuals are infected by a single airborne particle (even though numerous infectious particles can be emitted into the air and inhaled). Based on this theory, we propose a new epidemiological metric, regional relative risk, that compares the risk between two geographic regions (in theory, regions can range from individual rooms to large areas). Our modeling of transmission events predicts that for many scenarios of interest, minimal information is required to use this metric for locations 50 m to 20 km downwind. This prediction is consistent with data from prior disease outbreaks. Future efforts could apply and validate this theory for other spatial scales, such as indoor environments. Our results may be applicable to many airborne diseases a priori, as these results depend on the physics of airborne particulate dispersion.

Movement Mechanisms and Numerical Simulation of Virus-containing Exhaled Droplets

The problem of viral and microbial contamination has received extensive and high attention from scholars at home and abroad. A great deal of information and research has demonstrated that droplets containing organisms such as viruses and bacteria can be airborne, so it is extremely important to study the movement and transmission patterns of the particles. Human coughing and sneezing are the main sources of viral droplets and are the focus of this paper. This topic starts with a theoretical approach to investigate the propagation law of microbial aerosols in the air, combined with the characteristics of droplets, to establish a model of microbial particle dispersal. And based on the Lagrangian method, the model is simplified and the 4th order standard Runge-Kutta algorithm is used to numerically solve the differential equations based on the Matlab platform, so as to analyse the effects of factors such as jet velocity, ambient wind speed and the size of the exhaled virus particles occurring on the particle motion. The evaporation of particles also has a relatively large effect on the motion of smaller sized particles, which after complete evaporation will will float in the air and will no longer hit the ground. Ultimately, the analysis of particle movement distances leads to recommendations for the prevention of airborne infectious disease transmission.

Multi-Scale Airborne Infectious Disease Transmission.

Airborne disease transmission is central to many scientific disciplines including agriculture, veterinary biosafety, medicine, and public health. Legal and regulatory standards are in place to prevent agricultural, nosocomial, and community airborne disease transmission. However, the overall importance of the airborne pathway is underappreciated, e.g.,, US National Library of Medicine's Medical Subjects Headings (MESH) thesaurus lacks an airborne disease transmission indexing term. This has practical consequences as airborne precautions to control epidemic disease spread may not be taken when airborne transmission is important, but unrecognized. Publishing clearer practical methodological guidelines for surveillance studies and disease outbreak evaluations could help address this situation.To inform future work, this paper highlights selected, well-established airborne transmission events - largely cases replicated in multiple, independently conducted scientific studies. Methodologies include field experiments, modeling, epidemiology studies, disease outbreak investigations and mitigation studies. Collectively, this literature demonstrates that airborne viruses, bacteria, and fungal pathogens have the capability to cause disease in plants, animals, and humans over multiple distances - from near range (< 5 m) to continental (> 500 km) in scale. The plausibility and implications of undetected airborne disease transmission are discussed, including the notable underreporting of disease burden for several airborne transmitted diseases.

The Effect on Fit of Multiple Consecutive Donning and Doffing of N95 Filtering Facepiece Respirators.

N95 filtering facepiece respirators (FFRs) are widely used in healthcare to reduce transmission of airborne infectious diseases. These respirators are generally described as single use or limited reuse devices, but cost and operational issues mean that they may be donned and doffed multiple times. There is scant research on the effect of this practice on adequacy of fit. The purpose of this study was to measure the effect on respirator fit of multiple donning and doffing of N95 FFRs. This was an experiment in which 16 women and 9 men employed by the National Institute for Occupational Health (NIOH), Johannesburg, donned their same N95 FFR six times. All 25 were trained in the correct wearing of the devices before the experiment. Four models of respirators were used: the six who did not use respirators at work (novice subjects) were issued a 3M 1860 FFR and the others used their currently supplied one. During the experiment subjects donned their respirators under the supervision of the tester. Quantitative fit testing was done in the NIOH Occupational Hygiene laboratory after each donning according to the OSHA-Accepted Fit Test Protocol using the TSI PortaCount Pro+ Model 8038 Respirator Fit Tester. During the test, fit was measured after each of seven exercises and then an overall fit factor was computed. Only individuals who achieved an initial overall fit factor of ≥100 were allowed to continue participation in the study. Median overall fit factors were calculated for the 25 subjects for each donning and changes across them was examined using Wilcoxon rank sum tests. Men and women and frequent and infrequent users were compared across the six tests. Infrequent use was defined as subjects who wore respirators ≤ once per week, and novice subjects. Two subjects (8%) had an overall fit factor <100 at fit Test 2, 6 (24%) at Test 3, and 8 (32%) at Tests 4, 5, and 6. Thirteen respirator users (52%) achieved ≥100 throughout the fit testing, so 12 had at least one failure at either Tests 2-6. Five of the 12 subjects with at least one failure showed persistent failures on all subsequent donnings. Six subjects out of 12 (50%) who failed a fit test achieved an overall fit factor >100 at a subsequent test. There was a significant difference between the median first and sixth overall fit factors (195 versus 150; P = 0.0271), but not between the second and sixth (161 versus 150; P = 0.3584). Men and women had similar overall fit factors, but infrequent users had larger average overall fit factors than frequent users after all six donnings. Forty-eight percent of study subjects failed at least one fit test after re-donning an N95 FFR. The fit test data suggest that donning practices probably accounted for the fit test failures. The 50% of subjects who produced overall fit factors ≥100 after a test of <100 supports this contention.