Tracing the origin of large respiratory droplets by their deposition characteristics inside the respiratory tract during speech

Origin of differently sized respiratory droplets is fundamental for clarifying their viral loads and the sequential transmission mechanism of SARS-CoV-2 in indoor environments. Transient talking activities characterized by low (0.2 L/s), medium (0.9 L/s), and high (1.6 L/s) airflow rates of monosyllabic and successive syllabic vocalizations were investigated by computational fluid dynamics (CFD) simulations based on a real human airway model. SST k−ω model was chosen to predict the airflow field, and the discrete phase model (DPM) was used to calculate the trajectories of droplets within the respiratory tract. The results showed that flow field in the respiratory tract during speech is characterized by a significant laryngeal jet, and bronchi, larynx, and pharynx-larynx junction were main deposition sites for droplets released from the lower respiratory tract or around the vocal cords, and among which, over 90% of droplets over 5 µm released from vocal cords deposited at the larynx and pharynx-larynx junction. Generally, droplets' deposition fraction increased with their size, and the maximum size of droplets that were able to escape into external environment decreased with the airflow rate. This threshold size for droplets released from the vocal folds was 10–20 µm, while that for droplets released from the bronchi was 5–20 µm under various airflow rates. Besides, successive syllables pronounced at low airflow rates promoted the escape of small droplets, but do not significantly affect the droplet threshold diameter. This study indicates that droplets larger than 20 µm may entirely originate from the oral cavity, where viral loads are lower;it provides a reference for evaluating the relative importance of large-droplet spray and airborne transmission route of COVID-19 and other respiratory infections.

Tracing the origin of large respiratory droplets by their deposition characteristics inside the respiratory tract during speech.

Origin of differently sized respiratory droplets is fundamental for clarifying their viral loads and the sequential transmission mechanism of SARS-CoV-2 in indoor environments. Transient talking activities characterized by low (0.2 L/s), medium (0.9 L/s), and high (1.6 L/s) airflow rates of monosyllabic and successive syllabic vocalizations were investigated by computational fluid dynamics (CFD) simulations based on a real human airway model. SST k-ω model was chosen to predict the airflow field, and the discrete phase model (DPM) was used to calculate the trajectories of droplets within the respiratory tract. The results showed that flow field in the respiratory tract during speech is characterized by a significant laryngeal jet, and bronchi, larynx, and pharynx-larynx junction were main deposition sites for droplets released from the lower respiratory tract or around the vocal cords, and among which, over 90% of droplets over 5 µm released from vocal cords deposited at the larynx and pharynx-larynx junction. Generally, droplets' deposition fraction increased with their size, and the maximum size of droplets that were able to escape into external environment decreased with the airflow rate. This threshold size for droplets released from the vocal folds was 10-20 µm, while that for droplets released from the bronchi was 5-20 µm under various airflow rates. Besides, successive syllables pronounced at low airflow rates promoted the escape of small droplets, but do not significantly affect the droplet threshold diameter. This study indicates that droplets larger than 20 µm may entirely originate from the oral cavity, where viral loads are lower; it provides a reference for evaluating the relative importance of large-droplet spray and airborne transmission route of COVID-19 and other respiratory infections.

Effects of occupant behavior and ventilation on exposure to respiratory droplets in the indoor environment

To quantify the risk of the transmission of respiratory infections in indoor environments, we systematically assessed exposure to talking- and breathing-generated respiratory droplets in a generic indoor environment using computational fluid dynamic (CFD) simulations. The flow field in the indoor environment was obtained with SST k-ω model and Lagrangian method was used to predict droplet trajectories, where droplet evaporation was considered. Droplets can be categorized into small droplets (initial size ≤30 μm or ≤10 μm as droplet nuclei), medium droplets (30–80 μm) and large droplets (>100 μm) according to the exposure characteristics. Droplets up to 100 μm, particular the small ones, can contribute to both short-range and long-range airborne routes. For the face-to-face talking scenario, the intake fraction and deposition fractions of droplets on the face and facial mucosa of the susceptible were up to 4.96%, 2.14%, and 0.12%, respectively, indicating inhalation is the dominant route. The exposure risk from a talking infector decreases monotonically with the interpersonal distance, while that of nasal-breathing generated droplets maintains a relatively stable level within 1.0 m. Keeping an angle of 15° or above with the expiratory flow is efficient to reduce intake fractions to <0.37% for small droplets. Adjusting the orientation from face-to-face to face-to-back can reduce exposure to small droplets by approximately 88.0% during talking and 66.2% during breathing. A higher ventilation rate can reduce the risk of exposure to small droplets but may increase the risk of transmission via medium droplets by enhancing their evaporation rate. This study would serve as a fundamental research for epidemiologist, healthcare workers and the public in the purpose of infection control.

Exposure and respiratory infection risk via the short-range airborne route.

Leading health authorities have suggested short-range airborne transmission as a major route of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). However, there is no simple method to assess the short-range airborne infection risk or identify its governing parameters. We proposed a short-range airborne infection risk assessment model based on the continuum model and two-stage jet model. The effects of ventilation, physical distance and activity intensity on the short-range airborne exposure were studied systematically. The results suggested that increasing physical distance and ventilation reduced short-range airborne exposure and infection risk. However, a diminishing return phenomenon was observed when the ventilation rate or physical distance was beyond a certain threshold. When the infectious quantum concentration was less than 1 quantum/L at the mouth, our newly defined threshold distance and threshold ventilation rate were independent of quantum concentration. We estimated threshold distances of 0.59, 1.1, 1.7 and 2.6 m for sedentary/passive, light, moderate and intense activities, respectively. At these distances, the threshold ventilation was estimated to be 8, 20, 43, and 83 L/s per person, respectively. The findings show that both physical distancing and adequate ventilation are essential for minimising infection risk, especially in high-intensity activity or densely populated spaces.

Close contact behavior-based COVID-19 transmission and interventions in a subway system.

During COVID-19 pandemic, analysis on virus exposure and intervention efficiency in public transports based on real passenger's close contact behaviors is critical to curb infectious disease transmission. A monitoring device was developed to gather a total of 145,821 close contact data in subways based on semi-supervision learning. A virus transmission model considering both short- and long-range inhalation and deposition was established to calculate the virus exposure. During rush-hour, short-range inhalation exposure is 3.2 times higher than deposition exposure and 7.5 times higher than long-range inhalation exposure of all passengers in the subway. The close contact rate was 56.1 % and the average interpersonal distance was 0.8 m. Face-to-back was the main pattern during close contact. Comparing with random distribution, if all passengers stand facing in the same direction, personal virus exposure through inhalation (deposition) can be reduced by 74.1 % (98.5 %). If the talk rate was decreased from 20 % to 5 %, the inhalation (deposition) exposure can be reduced by 69.3 % (73.8 %). In addition, we found that virus exposure could be reduced by 82.0 % if all passengers wear surgical masks. This study provides scientific support for COVID-19 prevention and control in subways based on real human close contact behaviors.

Numerical investigation of airborne transmission of respiratory infections on the subway platform

Underground subway platforms are among the world’s busiest public transportation systems, but the airborne transmission mechanism of respiratory infections on these platforms has been rarely studied. Here, computational fluid dynamics (CFD) modeling is used to investigate the airflow patterns and infection risks in an island platform under two common ventilation modes: Mode 1- both sides have air inlets and outlets;Mode 2- air inlets are present at the two sides and outlets are present in the middle. Under the investigated scenario, airflow structure is characterized by the ventilation jet and human thermal plumes. Their interaction with the infector’s breathing jet imposes the front passenger under the highest exposure risk by short-range airborne route, with intake fractions up to 2.57% (oral breathing) or 0.63% (nasal breathing) under Mode 1;oral breathing of the infector may impose higher risks for the front passenger compared with nasal breathing. Pathogen are efficiently diluted as they travel further, in particular to adjacent crowds. The maximum and median value of intake fractions of passengers in adjacent crowds are respectively 0.093% and 0.016% (oral breathing), and 0.073% and 0.014% (nasal breathing) under Mode 1. Compared with Mode 1, the 2nd mode minimizes the interaction of ventilation jet and breathing jet, where the maximum intake fraction is only 0.34%, and the median value in the same crowd and other crowds are reduced by 23-63%. Combining published quanta generation rate data of COVID-19 and influenza infectors, the predicted maximum and median infection risks for passengers in the same crowds are respectively 1.46%−40.23% and 0.038%−1.67% during the 3−10 min waiting period, which are more sensitive to ventilation rate and exposure time compared with return air. This study can provide practical guidance for the prevention of respiratory infections in subway platforms.

Probable airborne transmission of SARS-CoV-2 in a poorly ventilated restaurant.

Although airborne transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been recognized, the condition of ventilation for its occurrence is still being debated. We analyzed a coronavirus disease 2019 (COVID-19) outbreak involving three families in a restaurant in Guangzhou, China, assessed the possibility of airborne transmission, and characterized the associated environmental conditions. We collected epidemiological data, obtained a full video recording and seating records from the restaurant, and measured the dispersion of a warm tracer gas as a surrogate for exhaled droplets from the index case. Computer simulations were performed to simulate the spread of fine exhaled droplets. We compared the in-room location of subsequently infected cases and spread of the simulated virus-laden aerosol tracer. The ventilation rate was measured using the tracer gas concentration decay method. This outbreak involved ten infected persons in three families (A, B, C). All ten persons ate lunch at three neighboring tables at the same restaurant on January 24, 2020. None of the restaurant staff or the 68 patrons at the other 15 tables became infected. During this occasion, the measured ventilation rate was 0.9 L/s per person. No close contact or fomite contact was identified, aside from back-to-back sitting in some cases. Analysis of the airflow dynamics indicates that the infection distribution is consistent with a spread pattern representative of long-range transmission of exhaled virus-laden aerosols. Airborne transmission of the SARS-CoV-2 virus is possible in crowded space with a ventilation rate of 1 L/s per person.

Probable Evidence of Fecal Aerosol Transmission of SARS-CoV-2 in a High-Rise Building.

BACKGROUND: The role of fecal aerosols in the transmission of severe acute respiratory syndrome coronavirus 2 has been suspected. OBJECTIVE: To investigate the temporal and spatial distributions of 3 infected families in a high-rise apartment building and examine the associated environmental variables to verify the role of fecal aerosols. DESIGN: Epidemiologic survey and quantitative reverse transcriptase polymerase chain reaction analyses on throat swabs from the participants; 237 surface and air samples from 11 of the 83 flats in the building, public areas, and building drainage systems; and tracer gas released into bathrooms as a surrogate for virus-laden aerosols in the drainage system. SETTING: A high-rise apartment building in Guangzhou, China. PARTICIPANTS: 9 infected patients, 193 other residents of the building, and 24 members of the building's management staff. MEASUREMENTS: Locations of infected flats and positive environmental samples, and spread of virus-laden aerosols. RESULTS: 9 infected patients in 3 families were identified. The first family had a history of travel to the coronavirus disease 2019 (COVID-19) epicenter Wuhan, whereas the other 2 families had no travel history and a later onset of symptoms. No evidence was found for transmission via the elevator or elsewhere. The families lived in 3 vertically aligned flats connected by drainage pipes in the master bathrooms. Both the observed infections and the locations of positive environmental samples are consistent with the vertical spread of virus-laden aerosols via these stacks and vents. LIMITATION: Inability to determine whether the water seals were dried out in the flats of the infected families. CONCLUSION: On the basis of circumstantial evidence, fecal aerosol transmission may have caused the community outbreak of COVID-19 in this high-rise building. PRIMARY FUNDING SOURCE: Key-Area Research and Development Program of Guangdong Province and the Research Grants Council of Hong Kong.

Multi-route transmission potential of SARS-CoV-2 in healthcare facilities.

Understanding the transmission mechanism of SARS-CoV-2 is a prerequisite to effective control measures. To investigate the potential modes of SARS-CoV-2 transmission, 21 COVID-19 patients from 12-47 days after symptom onset were recruited. We monitored the release of SARS-CoV-2 from the patients' exhaled breath and systematically investigated environmental contamination of air, public surfaces, personal necessities, and the drainage system. SARS-CoV-2 RNA was detected in 0 of 9 exhaled breath samples, 2 of 8 exhaled breath condensate samples, 1 of 12 bedside air samples, 4 of 132 samples from private surfaces, 0 of 70 samples from frequently touched public surfaces in isolation rooms, and 7 of 23 feces-related air/surface/water samples. The maximum viral RNA concentrations were 1857 copies/m3 in the air, 38 copies/cm2 in sampled surfaces and 3092 copies/mL in sewage/wastewater samples. Our results suggest that nosocomial transmission of SARS-CoV-2 can occur via multiple routes. However, the low detection frequency and limited quantity of viral RNA from the breath and environmental specimens may be related to the reduced viral load of the COVID-19 patients on later days after symptom onset. These findings suggest that the transmission dynamics of SARS-CoV-2 differ from those of SARS-CoV in healthcare settings.

Detection of Influenza and Other Respiratory Viruses in Air Sampled From a University Campus: A Longitudinal Study.

BACKGROUND: Respiratory virus-laden particles are commonly detected in the exhaled breath of symptomatic patients or in air sampled from healthcare settings. However, the temporal relationship of detecting virus-laden particles at nonhealthcare locations vs surveillance data obtained by conventional means has not been fully assessed. METHODS: From October 2016 to June 2018, air was sampled weekly from a university campus in Hong Kong. Viral genomes were detected and quantified by real-time reverse-transcription polymerase chain reaction. Logistic regression models were fitted to examine the adjusted odds ratios (aORs) of ecological and environmental factors associated with the detection of virus-laden airborne particles. RESULTS: Influenza A (16.9% [117/694]) and influenza B (4.5% [31/694]) viruses were detected at higher frequencies in air than rhinovirus (2.2% [6/270]), respiratory syncytial virus (0.4% [1/270]), or human coronaviruses (0% [0/270]). Multivariate analyses showed that increased crowdedness (aOR, 2.3 [95% confidence interval {CI}, 1.5-3.8]; P < .001) and higher indoor temperature (aOR, 1.2 [95% CI, 1.1-1.3]; P < .001) were associated with detection of influenza airborne particles, but absolute humidity was not (aOR, 0.9 [95% CI, .7-1.1]; P = .213). Higher copies of influenza viral genome were detected from airborne particles >4 µm in spring and <1 µm in autumn. Influenza A(H3N2) and influenza B viruses that caused epidemics during the study period were detected in air prior to observing increased influenza activities in the community. CONCLUSIONS: Air sampling as a surveillance tool for monitoring influenza activity at public locations may provide early detection signals on influenza viruses that circulate in the community.