Short-range airborne transmission of expiratory droplets between two people

Mapping full-range infection transmission from speaking, coughing, and sneezing in indoor environments and its impact on social distancing

Infectious respiratory diseases have posed significant threats to public health in the past decades. However, the full-range transmission in indoor environments remains unclear. In this study, we used the computational fluid dynamics (CFD) method with the large eddy simulation (LES) model, validated by particle image velocimetry (PIV) experiments, to explore the full-range transmission in an indoor space. The penetration of airborne droplets was divided into five power-law phases: accelerating jet (< 0.04-0.1 s, 0.3 m), decelerating jet (< 0.2-0.6 s, 0.7 m), puff (< 20 s, 2.2-3.8 m), mixing (< 360 s), and well-mixed phases (> 360 s). The maximum travel distance versus droplet diameter indicated "V" shapes, with minimum distances of 0.5-1.3 m for 100 µm droplets. The virus concentration decreased exponentially with distance and sustained high values within 2.8 m as a cone shape. The safe distance with an infection risk threshold of 10 % varied from 1 to 4 m, depending on viral load, dwell time, and mask. Here, we suggest social distances of 1, 1.8, and 4 m for the mask and asymptomatic cases, a short duration of viral loads < 107 #/mL, and a short duration of viral loads of 108-9 #/mL or long duration, respectively.

Optimal human respiratory simulation for exhaled gas based on CFD method

Human breathing is crucial for studying indoor environments and human health. Computational Fluid Dynamics (CFD) is a key tool for simulating human respiration. To enhance the accuracy of CFD simulations and reduce computation time, a new simulation strategy for human respiration is proposed in this paper. The effects of steady versus unsteady boundary conditions on simulation results were examined. For the unsteady boundary, sinusoidal exhalation velocities and non-inhalation gas were assumed, while the steady boundary involved constant velocities during both exhalation and inhalation phases. The jet center trajectory under different boundary conditions was analyzed and compared with experimental data. Additionally, variations in pollutant dispersion near the mouth under the two boundary conditions were discussed. Furthermore, the paper compared the calculation accuracy, calculation time and memory occupied by a single turbulence model or switching flow character models in human respiration simulation. Differences in exhaled gas vorticity and jet penetration depth across different flow models were identified. Finally, combined with the non-iterative algorithm, the optimal strategy of human respiration simulation was proposed. Results show that under the comprehensive consideration of calculation accuracy, calculation time and memory occupancy, using sinusoidal expiratory boundary conditions combined with the PISO algorithm, with the RNG k-ε model during expiratory phase, and switching into the laminar flow during inspiratory phase, is the optimal strategy of simulating human breathing.

What influences the close contact between health care workers and patients? An observational study in a hospital dental outpatient department

BACKGROUND

Dental outpatient departments, characterized by close proximity and unmasked patients, present a considerable risk of respiratory infections for health care workers (HCWs). However, the lack of comprehensive data on close contact (<1.5m) between HCWs and patients poses a significant obstacle to the development of targeted control strategies.

METHODS

An observation study was conducted at a hospital in Shenzhen, China, utilizing depth cameras with machine learning to capture close-contact behaviors of patients with HCWs. Additionally, questionnaires were administered to collect patient demographics.

RESULTS

The study included 200 patients, 10 dental practitioners, and 10 nurses. Patients had significantly higher close-contact rates with dental practitioners (97.5%) compared with nurses (72.8%, P < .001). The reason for the visit significantly influenced patient-practitioner (P = .018) and patient-nurse (P = .007) close-contact time, with the highest values observed in prosthodontics and orthodontics patients. Furthermore, patient age also significantly impacted the close-contact rate with nurses (P = .024), with the highest rate observed in patients below 14 years old at 85% [interquartile range: 70-93].

CONCLUSIONS

Dental outpatient departments exhibit high HCW-patient close-contact rates, influenced by visit purpose and patient age. Enhanced infection control measures are warranted, particularly for prosthodontics and orthodontics patients or those below 14 years old.

Ventilation does not affect close-range transmission of influenza virus in a ferret playpen setup

Sustained community spread of influenza viruses relies on efficient person-to-person transmission. Current experimental transmission systems do not mimic environmental conditions (e.g., air exchange rates, flow patterns), host behaviors, or exposure durations relevant to real-world settings. Therefore, results from these traditional systems may not be representative of influenza virus transmission in humans. To address this pitfall, we developed a close-range transmission setup that implements a play-based scenario and used it to investigate the impact of ventilation rates on transmission. In this setup, four immunologically naive recipient ferrets were exposed to a donor ferret infected with a genetically barcoded 2009 H1N1 virus (H1N1pdm09) for 4 h. The ferrets interacted in a shared space that included toys, similar to a childcare setting. Transmission efficiency was assessed under low and high ventilation, with air exchange rates of ~1.3 h-1 and 23 h-1, respectively. Transmission efficiencies observed in three independent replicate studies were similar between ventilation conditions. The presence of infectious virus or viral RNA on surfaces and in air throughout the exposure area was also not impacted by the ventilation rate. While high viral genetic diversity in donor ferret nasal washes was maintained during infection, recipient ferret nasal washes displayed low diversity, revealing a narrow transmission bottleneck regardless of ventilation rate. Examining the frequency and duration of ferret physical touches revealed no link between these interactions and a successful transmission event. Our findings indicate that exposures characterized by frequent, close-range interactions and the presence of fomites can overcome the benefits of increased ventilation.

Effect of an accelerating metro cabin on the diffusion of cough droplets

Coronaviruses being capable of spreading through droplet contamination have raised significant concerns regarding high-capacity public rail transport, such as the metro. Within a rapidly moving railcar cabin, the internal airflow lags behind the bulkhead, generating internally induced airflow that accelerates droplet dispersion within a non-inertial reference system. This study investigates the impact of acceleration on the diffusion of cough droplets of varying sizes using computational fluid dynamics. The modified k-ε equation in ANSYS® Fluent was utilized to simulate droplet diffusion under different body orientations by adjusting the inertial force correction source term. Results indicate that droplets in the middle size range (50-175 μm) are primarily influenced by inertial forces, whereas smaller droplets (3.5-20 μm) are predominantly controlled by air drag forces. Regardless of facial orientation, the outlet of high-capacity public rail transport poses the highest risk of infection.

COVID-19 transmission and control in land public transport: A literature review

Land public transport is an important link within and between cities, and how to control the transmission of COVID-19 in land public transport is a critical issue in our daily lives. However, there are still many inconsistent opinions and views about the spread of SARS-CoV-2 in land public transport, which limits our ability to implement effective interventions. The purpose of this review is to overview the literature on transmission characteristics and routes of the epidemic in land public transport, as well as to investigate factors affecting its spread and provide feasible measures to mitigate the infection risk of passengers. We obtained 898 papers by searching the Web of Science, Pubmed, and WHO global COVID database by keywords, and finally selected 45 papers that can address the purpose of this review. Land public transport is a high outbreak area for COVID-19 due to characteristics like crowding, inadequate ventilation, long exposure time, and environmental closure. Different from surface touch transmission and drop spray transmission, aerosol inhalation transmission can occur not only in short distances but also in long distances. Insufficient ventilation is the most important factor influencing long-distance aerosol transmission. Other transmission factors (e.g., interpersonal distance, relative orientation, and ambient conditions) should be noticed as well, which have been summarized in this paper. To address various influencing factors, it is essential to suggest practical and efficient preventive measures. Among these, increased ventilation, particularly the fresh air (i.e., natural ventilation), has proven to effectively reduce indoor infection risk. Many preventive measures are also effective, such as enlarging social distance, avoiding face-to-face orientation, setting up physical partitions, disinfection, avoiding talking, and so on. As research on the epidemic has intensified, people have broken down many perceived barriers, but more comprehensive studies on monitoring systems and prevention measures in land public transport are still needed.

Airborne respiratory aerosol transport and deposition in a two-person office using a novel diffusion-based numerical model

BACKGROUND

The COVID-19 pandemic was caused by the SARS-CoV-2 coronaviruses transmitted mainly through exposure to airborne respiratory droplets and aerosols carrying the virus.

OBJECTIVE

To assess the transport and dispersion of respiratory aerosols containing the SARS-CoV-2 virus and other viruses in a small office space using a diffusion-based computational modeling approach.

METHODS

A 3-D computational model was used to simulate the airflow inside the 70.2 m3 ventilated office. A novel diffusion model accounting for turbulence dispersion and gravitational sedimentation was utilized to predict droplet concentration transport and deposition. The numerical model was validated and used to investigate the influences of partition height and different ventilation rates on the concentration of respiratory aerosols of various sizes (1, 10, 20, and 50 µm) emitted by continuous speaking.

RESULTS

An increase in the hourly air change rate (ACH) from 2.0 to 5.6 decreased the 1 μm droplet concentration inside the office by a factor of 2.8 and in the breathing zone of the receptor occupant by a factor of 3.2. The concentration at the receptor breathing zone is estimated by the area-weighted average of a 1 m diameter circular disk, with its centroid at the center of the receptor mannequin mouth. While all aerosols were dispersed by airflow turbulence, the gravitational sedimentation significantly influenced the transport of larger aerosols in the room. The 1 and 10 μm aerosols remained suspended in the air and dispersed throughout the room. In contrast, the larger 20 and 50 μm aerosols deposited on the floor quickly due to the gravitational sedimentation. Increasing the partition between cubicles by 0.254 m (10") has little effect on the smaller aerosols and overall exposure.

IMPACT

This paper provides an efficient computational model for analyzing the concentration of different respiratory droplets and aerosols in an indoor environment. Thus, the approach could be used for assessing the influence of the spatial concentration variations on exposure for which the fully mixed model cannot be used.

Three dimensional analysis of the exhalation flow in the proximity of the mouth

The human exhalation flow is characterized in this work from the three-dimensional velocimetry results obtained by using the stereo particle image velocimetry (SPIV) measurement technique on the flow emitted from a realistic airway model. For this purpose, the transient exhalation flow through the mouth of a person performing two different breaths corresponding to two metabolic rates, standing relaxed (SR) and walking active (WA), is emulated and studied. To reproduce the flow realistically, a detailed three-dimensional model obtained from computed tomography measurements on real subjects is used. To cope with the variability of the experimental data, a subsequent analysis of the results is performed using the TR-PIV (time resolved particle image velocimetry) technique. Exhalation produces a transient jet that becomes a puff when flow emission ends. Three-dimensional vector fields of the jet velocity are obtained in five equally spaced transverse planes up to a distance of Image 1 from the mouth at equally spaced time instants Image 2 which will be referred to as phases (φ), from the beginning to the end of exhalation. The time evolution during exhalation of the jet area of influence, the velocity field and the jet air entrainment have been characterized for each of the jet cross sections. The importance of the use of realistic airway models for the study of this type of flow and the influence of the metabolic rate on its development are also analyzed. The results obtained contribute to the characterization of the human exhalation as a pathway of the transmission of pathogens such as SARS-CoV-2 virus.

Airborne SARS-CoV2 virus exposure, interpersonal distance, face mask and perceived risk of infection

Participants judged the risk of an infection during a face to face conversation at different interpersonal distances from a SARS-CoV-2 infected person who wore a face mask or not, and in the same questionnaire answered questions about Corona related issues. Keeping a distance to an infected person serves as a protective measure against an infection. When an infected person moves closer, risk of infection increases. Participants were aware of this fact, but underestimated the rate at which the risk of infection increases when getting closer to an infected person, e.g., from 1.5 to 0.5 m (perceived risk increase = 3.33 times higher, objective = 9.00 times higher). This is alarming because it means that people can take risks of infection that they are not aware of or want to take, when they approach another possibly virus infected person. Correspondingly, when an infected person moves away the speed of risk decrease was underestimated, meaning that people are not aware of how much safer they will be if they move away from an infected person. The perceived risk reducing effects of a face mask were approximately correct. Judgments of infection risk at different interpersonal distances (with or without a mask) were unrelated to how often a person used a mask, avoided others or canceled meetings during the COVID-19 pandemic. Greater worry in general and in particular over COVID-19, correlated positively with more protective behavior during the pandemic, but not with judgments of infection risk at different interpersonal distances. Participants with higher scores on a cognitive numeracy test judged mask efficiency more correctly, and women were more worried and risk avoiding than men. The results have implications for understanding behavior in a pandemic, and are relevant for risk communications about the steep increase in risk when approaching a person who may be infected with an airborne virus.

Epidemic exposure risk assessment in digital contact tracing: A fuzzy logic approach

Background

Bluetooth low energy (BLE)-based contact-tracing applications were widely used during the COVID-19 pandemic. However, the use of only the received signal strength feature for proximity calculations may not be adaptable to different virus variants or scalable for other potential epidemic diseases.

Objective

This study presents a novel framework in regard to evaluating and classifying personal exposure risk that considers both contact features, which include distance and length of contact, and environment features, which include crowd size and the number of recently infected cases in the environment. The framework utilizes a fuzzy expert system that is adaptable to different virus variants.

Methods

The proposed method was tested on two viruses with different close contact features, which used four membership functions and 256 fuzzy rule sets.

Results

The proposed framework classified personal exposure risks into four classes, which include low, medium, high, and too high risk. The empirical results showed that the fuzzy logic-based approach reduced the number of false positive cases and demonstrated better accuracy and precision than the current BLE-only approaches.

Conclusions

The proposed framework provides a more practical and adaptable method in regard to assessing exposure risks in real-world scenarios. It has the potential to be scalable and adaptable to different virus variants and other potential epidemic diseases by considering both contact and environment features. These findings may be useful in order to develop more effective digital contact-tracing applications and policies.

Intranasal mask for protecting the respiratory tract against viral aerosols

The spread of many infectious diseases relies on aerosol transmission to the respiratory tract. Here we design an intranasal mask comprising a positively-charged thermosensitive hydrogel and cell-derived micro-sized vesicles with a specific viral receptor. We show that the positively charged hydrogel intercepts negatively charged viral aerosols, while the viral receptor on vesicles mediates the entrapment of viruses for inactivation. We demonstrate that when displaying matched viral receptors, the intranasal masks protect the nasal cavity and lung of mice from either severe acute respiratory syndrome coronavirus 2 or influenza A virus. With computerized tomography images of human nasal cavity, we further conduct computational fluid dynamics simulation and three-dimensional printing of an anatomically accurate human nasal cavity, which is connected to human lung organoids to generate a human respiratory tract model. Both simulative and experimental results support the suitability of intranasal masks in humans, as the likelihood of viral respiratory infections induced by different variant strains is dramatically reduced.

Social Distance Approximation on Public Transport Using Stereo Depth Camera and Passenger Pose Estimation

In order to effectively balance enforced guidance/regulation during a pandemic and limit infection transmission, with the necessity for public transportation services to remain safe and operational, it is imperative to understand and monitor environmental conditions and typical behavioural patterns within such spaces. Social distancing ability on public transport as well as the use of advanced computer vision techniques to accurately measure this are explored in this paper. A low-cost depth-sensing system is deployed on a public bus as a means to approximate social distancing measures and study passenger habits in relation to social distancing. The results indicate that social distancing on this form of public transport is unlikely for an individual beyond a 28% occupancy threshold, with an 89% chance of being within 1-2 m from at least one other passenger and a 57% chance of being within less than one metre from another passenger at any one point in time. Passenger preference for seating is also analysed, which clearly demonstrates that for typical passengers, ease of access and comfort, as well as seats having a view, are preferred over maximising social-distancing measures. With a highly detailed and comprehensive set of acquired data and accurate measurement capability, the employed equipment and processing methodology also prove to be a robust approach for the application.

Trends in the numbers of SARS-CoV-2 infections among students: a prospective cohort study comparing students in sports boarding schools with students in day schools during early COVID-19 pandemic

Introduction

During the first months of the COVID pandemic it emerged that facilities where people gather or live together in cohorts, such as nursing homes or schools, were particularly at high risk for becoming hotspots of virus transmission. German political and health institutions responded with far-reaching interventions and preventive strategies to protect the population from infection with SARS-CoV-2. In this context, it remains unclear whether boarding schools for sports particularly pose a risk of infection to their residents.

Methods

In a single-center prospective cohort study, numbers of SARS-CoV-2 infections of students in sports boarding schools (n = 11) vs. students attending regular day schools (n = 22) in the region Freiburg/Hochschwarzwald in Germany were investigated over a period from October 2020 to January 2021 via regular virus and antibody screening (German Clinical Trials Register; Study ID: DRKS00021909). In addition, individual and behavioral risk factors for infection were stratified via questionnaire, which provide an indication of cohort specific risk factors for infection and the success of the implementation of hygiene concepts, as well as other infection prevention strategies, within the respective facilities.

Results

Regarding SARS-CoV-2 infection numbers, the screening detected no significant group difference between sports boarding schools vs. day schools.

Discussion

The study results provide indications that sports boarding schools did not pose an increased risk of infection, assuming that the facilities prevent virus transmissions with appropriate preventive strategies and hygiene measures. In future pandemic scenarios larger-scale and multicenter studies are necessary to achieve more comprehensive epidemiological data in this field.

Increasing rhinovirus prevalence in paediatric intensive care patients since the SARS-CoV2 pandemic

BACKGROUND

Rhinovirus (HRV) is a significant seasonal pathogen in children. The emergence of SARS-CoV2, and the social restrictions introduced in, disrupted viral epidemiology. Here we describe the experience of Great Ormond Street Hospital (GOSH), where HRV almost entirely disappeared from the paediatric intensive care units (PICU) during the first national lockdown and then rapidly re-emerged with a fast-increasing incidence, leading to concerns about possible nosocomial transmission in a vulnerable population.

OBJECTIVES

To describe alterations in HRV infection amongst PICU patients at GOSH since the emergence of SARS-COV2 STUDY DESIGN: 10,950 nasopharyngeal aspirate viral PCR samples from GOSH PICU patients from 2019 to 2023 were included. 3083 returned a positive result for a respiratory virus, with 1530 samples positive for HRV. 66 HRV isolates from August 2020 - Jan 2021, the period of rapidly increasing HRV incidence, were sequenced. Electronic health record data was retrospectively collected for the same period.

RESULTS

Following a reduction in the incidence of HRV infection during the first national lockdown, multiple genotypes of HRV emerged amongst GOSH PICU patients, with the incidence of HRV infection rapidly surging to levels higher than that seen prior to the emergence of SARS-CoV2 and continuing to circulate at increased incidence year-round.

CONCLUSIONS

The incidence of HRV infection amongst GOSH PICU patients is markedly higher than prior to the emergence of SARS-CoV2, a pattern not seen in other respiratory viruses. The increased burden of HRV-infection in vulnerable PICU patients has both clinical and infection prevention and control Implications.

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.

Transmission of droplet aerosols in an elevator cabin: Effect of the ventilation mode

The recent outbreak of COVID-19 has threatened public health. Owing to the relatively sealed environment and poor ventilation in elevator cabins, passengers are at risk of respiratory tract infection. However, the distribution and dispersion of droplet aerosols in elevator cabins remain unclear. This study investigated the transmission of droplet aerosols exhaled by a source patient under three ventilation modes. Droplet aerosols produced by nose breathing and mouth coughing were resolved using computational fluid dynamics (CFD) simulations. We adopted the verified renormalization group (RNG) k-ε turbulence model to simulate the flow field and the Lagrangian method to track the droplet aerosols. In addition, the influence of the ventilation mode on droplet transmission was evaluated. The results showed that droplet aerosols gathered in the elevator cabin and were difficult to discharge under the mixed and displacement ventilation modes with specific initial conditions. The inhalation proportion of droplet aerosols for air curtain was 0.016%, which was significantly lower than that for mixed ventilation (0.049%) and displacement ventilation (0.071%). The air curtain confined the transmission of droplet aerosols with the minimum ratios of inhalation, deposition, and suspension and is thus recommended to reduce the exposure risk.

Student close contact behavior and COVID-19 transmission in China's classrooms

Classrooms are high-risk indoor environments, so analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in classrooms is important for determining optimal interventions. Due to the absence of human behavior data, it is challenging to accurately determine virus exposure in classrooms. A wearable device for close contact behavior detection was developed, and we recorded >250,000 data points of close contact behaviors of students from grades 1 to 12. Combined with a survey on students' behaviors, we analyzed virus transmission in classrooms. Close contact rates for students were 37 ± 11% during classes and 48 ± 13% during breaks. Students in lower grades had higher close contact rates and virus transmission potential. The long-range airborne transmission route is dominant, accounting for 90 ± 3.6% and 75 ± 7.7% with and without mask wearing, respectively. During breaks, the short-range airborne route became more important, contributing 48 ± 3.1% in grades 1 to 9 (without wearing masks). Ventilation alone cannot always meet the demands of COVID-19 control; 30 m3/h/person is suggested as the threshold outdoor air ventilation rate in a classroom. This study provides scientific support for COVID-19 prevention and control in classrooms, and our proposed human behavior detection and analysis methods offer a powerful tool to understand virus transmission characteristics and can be employed in various indoor environments.

Numerical study of transient indoor airflow and virus-laden droplet dispersion: Impact of interactive human movement

Human movement affects indoor airflow and the airborne transmission of respiratory infectious diseases, which has attracted scholars. However, the interactive airflow between moving and stationary people has yet to be studied in detail. This study used the numerical method validated by experimental data to explore the transient indoor airflow and virus-laden droplet dispersion in scenes with interactive human movement. Human-shaped numerical models and the dynamic mesh method were adopted to realize human movement in scenes with different lateral distances (0.2-1.2 m) between a moving person and stationary (standing/sitting) persons. The interactive human movement obviously impacts other persons' respiratory airflow, and the lateral fusion ranged about 0.6 m. The interactive human movement strengthens the indoor airflow convection, and some exhaled virus-laden droplets were carried into wake flow and enhanced long-range airborne transmission. The impact of interactive human movement on sitting patients' exhalation airflow seems more evident than on standing patients. The impact might last over 2 min after movement stopped, and people in the affected area might be at a higher exposure. The results can provide a reference for epidemic control in indoor environments.

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.

CFD Simulations of Ventilation and Interunit Dispersion in Dormitory Complex: A Case Study of Epidemic Outbreak in Shanghai

Since the beginning of March 2022, a new round of COVID-19 outbreaks in Shanghai has led to a sharp increase in the number of infected people. It is important to identify possible pollutant transmission routes and predict potential infection risks for infectious diseases. Therefore, this study investigated the cross-diffusion of pollutants caused by natural ventilation, including external windows and indoor ventilation windows, under three wind directions in a densely populated building environment with the CFD method. In this study, CFD building models were developed based on an actual dormitory complex and surrounding buildings under realistic wind conditions to reproduce the airflow fields and transmission paths of pollutants. This paper adopted the Wells-Riley model to assess the risk of cross-infection. The biggest risk of infection was when a source room was located on the windward side, and the risk of infection in other rooms on the same side as the source room was large in the windward direction. When pollutants were released from room 8, north wind resulted in the highest concentration of pollutants in room 28, reaching 37.8%. This paper summarizes the transmission risks related to the indoor and outdoor environments of compact buildings.

The Influence of Ventilation Measures on the Airborne Risk of Infection in Schools: A Scoping Review

OBJECTIVES

To review the risk of airborne infections in schools and evaluate the effect of intervention measures reported in field studies.

BACKGROUND

Schools are part of a country's critical infrastructure. Good infection prevention measures are essential for reducing the risk of infection in schools as much as possible, since these are places where many individuals spend a great deal of time together every weekday in a small area where airborne pathogens can spread quickly. Appropriate ventilation can reduce the indoor concentration of airborne pathogens and reduce the risk of infection.

METHODS

A systematic search of the literature was conducted in the databases Embase, MEDLINE, and ScienceDirect using keywords such as school, classroom, ventilation, carbon dioxide (CO2) concentration, SARS-CoV-2, and airborne transmission. The primary endpoint of the studies selected was the risk of airborne infection or CO2 concentration as a surrogate parameter. Studies were grouped according to the study type.

RESULTS

We identified 30 studies that met the inclusion criteria, six of them intervention studies. When specific ventilation strategies were lacking in schools being investigated, CO2 concentrations were often above the recommended maximum values. Improving ventilation lowered the CO2 concentration, resulting in a lower risk of airborne infections.

CONCLUSIONS

The ventilation in many schools is not adequate to guarantee good indoor air quality. Ventilation is an important measure for reducing the risk of airborne infections in schools. The most important effect is to reduce the time of residence of pathogens in the classrooms.

Conversational head movement decreases close-contact exposure to expired respiratory droplets

People constantly move their heads during conversation, as such movement is an important non-verbal mode of communication. Head movement alters the direction of people's expired air flow, therefore affecting their conversational partners' level of exposure. Nevertheless, there is a lack of understanding of the mechanism whereby head movement affects people's exposure. In this study, a dynamic meshing method in computational fluid dynamics was used to simulate the head movement of a human-shaped thermal manikin. Droplets were released during the oral expiration periods of the source manikin, during which it was either motionless, was shaking its head or was nodding its head, while the head of a face-to-face target manikin remained motionless. The results indicate that the target manikin had a high level of exposure to respiratory droplets when the source manikin was motionless, whereas the target manikin's level of exposure was significantly reduced when the source manikin was shaking or nodding its head. The source manikin had the highest level of self-exposure when it was nodding its head and the lowest level of self-exposure when its head was motionless. People's level of exposure during close contact is highly variable, highlighting the need for further investigations in more realistic conversational scenarios.

Numerical modeling of a sneeze, a cough and a continuum speech inside a hospital lift

The global COVID-19 and its variants put us on notice of the importance of studying the spread of respiratory diseases. The most common means of propagation was the emission of droplets due to different respiration activities. This study modeled by computational fluid dynamics (CFD) techniques a high risk scenario like a hospital elevator. The cabin was provided with an extraction fan and a rack for air renewal. Inside, a sneeze, a cough and a continuum speech were simulated. Inside the lift, two occupants were introduced to observe the risk of propagation of emitted droplets and the impact in diseases spreading risk. The fan effectivity over the droplets ejection was analyzed, as well as environmental condition of a clinical setting. For this purpose the amount of droplets inside were counted during whole time of simulations. The effect of the fan was concluded as able to eject the 60% of small droplets, but also a high performance in spreading particles inside. Among the three cases, the riskiest scenario was the continuum speech due to the saturation of droplets in airborne.

Predominance of inhalation route in short-range transmission of respiratory viruses: Investigation based on computational fluid dynamics

During the Coronavirus disease 2019 pandemic, short-range virus transmission has been observed to have a higher risk of causing infection than long-range virus transmission. However, the roles played by the inhalation and large droplet routes cannot be distinguished in practice. A recent analytical study revealed the predominance of short-range inhalation over the large droplet spray route as causes of respiratory infections. In the current study, short-range exposure was analyzed via computational fluid dynamics (CFD) simulations using a discrete phase model. Detailed facial membranes, including eyes, nostrils, and a mouth, were considered. In CFD simulations, there is no need for a spherical approximation of the human head for estimating deposition nor the "anisokinetic aerosol sampling" approximation for estimating inhalation in the analytical model. We considered two scenarios (with two spheres [Scenario 1] and two human manikins [Scenario 2]), source-target distances of 0.2 to 2 m, and droplet diameters of 3 to 1,500 µm. The overall CFD exposure results agree well with data previously obtained from a simple analytical model. The CFD results confirm the predominance of the short-range inhalation route beyond 0.2 m for expiratory droplets smaller than 50 µm during talking and coughing. A critical droplet size of 87.5 µm was found to differentiate droplet behaviors. The number of droplets deposited on the target head exceeded those exposed to facial membranes, which implies a risk of exposure through the immediate surface route over a short range.

Electronic Supplementary Material ESM

the Supplementary Materials are available in the online version of this article at 10.1007/s12273-022-0968-y.

Event-Specific Transmission Forecasting of SARS-CoV-2 in a Mixed-Mode Ventilated Office Room Using an ANN

The emerging novel variants and re-merging old variants of SARS-CoV-2 make it critical to study the transmission probability in mixed-mode ventilated office environments. Artificial neural network (ANN) and curve fitting (CF) models were created to forecast the R-Event. The R-Event is defined as the anticipated number of new infections that develop in particular events occurring over the course of time in any defined space. In the spring and summer of 2022, real-time data for an office environment were collected in India in a mixed-mode ventilated office space in a composite climate. The performances of the proposed CF and ANN models were compared with respect to traditional statistical indicators, such as the correlation coefficient, RMSE, MAE, MAPE, NS index, and a20-index, in order to determine the merit of the two approaches. Thirteen input features, namely the indoor temperature (TIn), indoor relative humidity (RHIn), area of opening (AO), number of occupants (O), area per person (AP), volume per person (VP), CO2 concentration (CO2), air quality index (AQI), outer wind speed (WS), outdoor temperature (TOut), outdoor humidity (RHOut), fan air speed (FS), and air conditioning (AC), were selected to forecast the R-Event as the target. The main objective was to determine the relationship between the CO2 level and R-Event, ultimately producing a model for forecasting infections in office building environments. The correlation coefficients for the CF and ANN models in this case study were 0.7439 and 0.9999, respectively. This demonstrates that the ANN model is more accurate in R-Event prediction than the curve fitting model. The results show that the proposed ANN model is reliable and significantly accurate in forecasting the R-Event values for mixed-mode ventilated offices.

Perceived Corona virus exposure as a function of interpersonal distance and time of a conversation

BACKGROUND

During the COVID-19 pandemic people were asked to keep interpersonal distance, wash their hands and avoid gatherings of people. But, do people understand how much a change of the distance to a virus infected person means for the exposure to that person's virus? To answer this question, we studied how people perceive virus exposure from an infected person at different distances and lengths of a conversation.

METHOD

An online questionnaire was distributed to 101 participants drawn from the general US population. Participants judged perceived virus exposure at different interpersonal distances to an infected person in a face to face conversation of different lengths of time. A model based on empirical and theoretical studies of dispersion of particles in the air was used to estimate a person's objective virus exposure during different times and distances from a virus source. The model and empirical data show that exposure changes with the square of the distance and linearly with time.

RESULTS

A majority (78%) of the participants underestimated the effects on virus exposure following a change of interpersonal distance. The dominating bias was assuming that exposure varies linearly with distance. To illustrate, an approach to a virus source from 6 to 2 feet was judged to give a 3 times higher exposure but, objectively it is 9 times. By way of contrast, perceptions of exposure as a function of the duration of a conversation were unbiased. The COVID-19 pandemic caused by the SARS-CoV2 virus is likely to be followed by other pandemics also caused by airborne Corona or other viruses. Therefore, the results are important for administrators when designing risk communications to the general public and workers in the health care sector about social distancing and infection risks.

CONCLUSIONS

People quite drastically underestimate the increase in virus exposure following an approach to a virus infected person. They also overestimate exposure after a move away from an infected person. For public health reasons, the correct function connecting distance with virus exposure should be communicated to the general public to avoid deliberate violations of recommended interpersonal distances.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s44155-022-00027-9.

Airborne transmission of biological agents within the indoor built environment: a multidisciplinary review

The nature and airborne dispersion of the underestimated biological agents, monitoring, analysis and transmission among the human occupants into building environment is a major challenge of today. Those agents play a crucial role in ensuring comfortable, healthy and risk-free conditions into indoor working and leaving spaces. It is known that ventilation systems influence strongly the transmission of indoor air pollutants, with scarce information although to have been reported for biological agents until 2019. The biological agents' source release and the trajectory of airborne transmission are both important in terms of optimising the design of the heating, ventilation and air conditioning systems of the future. In addition, modelling via computational fluid dynamics (CFD) will become a more valuable tool in foreseeing risks and tackle hazards when pollutants and biological agents released into closed spaces. Promising results on the prediction of their dispersion routes and concentration levels, as well as the selection of the appropriate ventilation strategy, provide crucial information on risk minimisation of the airborne transmission among humans. Under this context, the present multidisciplinary review considers four interrelated aspects of the dispersion of biological agents in closed spaces, (a) the nature and airborne transmission route of the examined agents, (b) the biological origin and health effects of the major microbial pathogens on the human respiratory system, (c) the role of heating, ventilation and air-conditioning systems in the airborne transmission and (d) the associated computer modelling approaches. This adopted methodology allows the discussion of the existing findings, on-going research, identification of the main research gaps and future directions from a multidisciplinary point of view which will be helpful for substantial innovations in the field.

Risk assessment of COVID-19 infection for subway commuters integrating dynamic changes in passenger numbers

The COVID-19 global pandemic has had a significant impact on mass travel. We examined the risk of transmission of COVID-19 infection between subway commuters using the Susceptible Exposed Infected Recovered (SEIR) model. The model considered factors that may influence virus transmission, namely subway disinfection, ventilation capacity, average commuter spacing, single subway journey time, COVID-19 transmission capacity, and dynamic changes in passenger numbers. Based on these parameters, above a certain threshold (25 min), the risk of infection for susceptible people increased significantly as journey time increased. Average distance between commuters and levels of ventilation and disinfection were also important influencing factors. Meanwhile, the model also indicated that the risk of infection varied at different times of the day. Therefore, this paper recommends strengthening ventilation and disinfection in the carriages and limiting the time of single journeys, with an average distance of at least 1 m between passengers. In this light, subway commuters need to take proactive precautions to reduce their risk of COVID-19 infection. Also, the results show the importance of managing subway stations efficiently during epidemic and post-epidemic eras.

Effects of Return Air Inlets' Location on the Control of Fine Particle Transportation in a Simulated Hospital Ward

The COVID-19 pandemic has made significant impacts on public health, including human exposure to airborne pathogens. In healthcare facilities, the locations of return air vents in ventilation systems may have important effects on lowering airborne SARS-CoV-2 transmission. This study conducted experiments to examine the influence of different return air vents' heights (0.7 m, 1.2 m, and 1.6 m) on the particle removal effects in a simulated patient ward. Three different ventilation systems were examined: top celling air supply-side wall return (TAS), underfloor air supply-side wall return (UFAS) and side wall air supply-side wall return (SAS). CFD simulation was applied to further study the effects of return air inlets' heights (0.3 m, 0.7 m, 1.2 m, 1.6 m, and 2.0 m) and air exchange rates. The technique for order of preference by similarity to ideal solution (TOPSIS) analysis was used to calculate the comprehensive scores of 60 scenarios using a multi-criterion method to obtain the optimal return air inlets' heights. Results showed that for each additional 0.5 m distance in most working conditions, the inhalation fraction index of medical staff could be reduced by about 5-20%. However, under certain working conditions, even though the distances between the patients and medical personnel were different, the optimal heights of return air vents were constant. For TAS and UFAS, the optimal return air inlets' height was 1.2 m, while for SAS, the best working condition was 1.6 m air supply and 0.7 m air return. At the optimum return air heights, the particle decay rate per hour of SAS was 75% higher than that of TAS, and the rate of particle decay per hour of SAS was 21% higher than that of UFAS. The location of return air inlets could further affect the operating cost-effectiveness of ventilation systems: the highest operating cost-effectiveness was 8 times higher than the lowest one.

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

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

Forecasting the transmission trends of respiratory infectious diseases with an exposure-risk-based model at the microscopic level

Respiratory infectious diseases (e.g., COVID-19) have brought huge damages to human society, and the accurate prediction of their transmission trends is essential for both the health system and policymakers. Most related studies focus on epidemic trend forecasting at the macroscopic level, which ignores the microscopic social interactions among individuals. Meanwhile, current microscopic models are still not able to sufficiently decipher the individual-based spreading process and lack valid quantitative tests. To tackle these problems, we propose an exposure-risk-based model at the microscopic level, including 4 modules: individual movement, virion-laden droplet movement, individual exposure risk estimation, and prediction of transmission trends. Firstly, the front two modules reproduce the movements of individuals and the droplets of infectors' expiratory activities, respectively. Then, the outputs are fed to the third module to estimate the personal exposure risk. Finally, the number of new cases is predicted in the final module. By predicting the new COVID- 19 cases in the United States, the performances of our model and 4 other existing macroscopic or microscopic models are compared. Specifically, the mean absolute error, root mean square error, and mean absolute percentage error provided by the proposed model are respectively 2454.70, 3170.51, and 3.38% smaller than the minimum results of comparison models. The quantitative results reveal that our model can accurately predict the transmission trends from a microscopic perspective, and it can benefit the further investigation of many microscopic disease transmission factors (e.g., non-walkable areas and facility layouts).

Multi-person movement-induced airflow and the effects on virus-laden expiratory droplet dispersion in indoor environments

The multi-person movement might cause complex induced airflow and affect the virus-laden expiratory droplet transmission in indoor environments. Using the dynamic mesh model in computational fluid dynamics, the multi-person movement with different personnel location distributions was realized. The induced airflow patterns, virus-laden droplet dispersion, and concentration distribution were investigated in detail. The results show that multi-person movement might intensify inter-regional convection, which has been rarely found in single-person movement conditions. Side-by-side distribution and ladder distribution of moving persons could cause a connected low-pressure area behind the moving persons, which might enhance lateral virus transport, especially where droplets might suspend at the height of the breathing zone. Not only 1-10 μm aerosols but also some 20-50 μm droplets are carried by the multi-person movement-induced airflow to over 3 m. Since the width of induced airflow is about 0.6-1.0 m, moving persons should keep enough horizontal distance (>1.0 m) to limit the air mixing and virus-laden droplet transmission. This paper could provide a detailed reference for the numerical study of multi-person movement-induced airflow patterns, droplet dispersion, and indoor infection control.

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.

Transmission characteristics of respiratory droplets aerosol in indoor environment: an experimental study

Transmission of droplets has been recognized as an important form of infection for the respiratory diseases. This study investigated the distribution of human respiratory droplets and assessed the effects of air change rate and generated velocity on droplet transmission using an active agent in an enclosed chamber (46 m³). Results revealed that the higher the air change rate was, the fewer viable droplets were detected in the range of <3.3 μm with ventilation; an increased air change rate can increase the attenuation of droplet aerosol. Without ventilation, the viable droplet size was observed to mainly distribute greater than 3.3 μm, which occupied up 87.5% of the total number. When the generated velocity was increased to 20 m/s, 29.38% of the viable droplets were detected at the position of 2.0 m. The findings are excepted to be useful for developing the technology of reducing droplet propagation and providing data verification for simulation research.

Role of pathogen-laden expiratory droplet dispersion and natural ventilation explaining a COVID-19 outbreak in a coach bus

The influencing mechanism of droplet transmissions inside crowded and poorly ventilated buses on infection risks of respiratory diseases is still unclear. Based on experiments of one-infecting-seven COVID-19 outbreak with an index patient at bus rear, we conducted CFD simulations to investigate integrated effects of initial droplet diameters(tracer gas, 5 μm, 50 μm and 100 μm), natural air change rates per hour(ACH = 0.62, 2.27 and 5.66 h-1 related to bus speeds) and relative humidity(RH = 35% and 95%) on pathogen-laden droplet dispersion and infection risks. Outdoor pressure difference around bus surfaces introduces natural ventilation airflow entering from bus-rear skylight and leaving from the front one. When ACH = 0.62 h-1(idling state), the 30-min-exposure infection risk(TIR) of tracer gas is 15.3%(bus rear) - 11.1%(bus front), and decreases to 3.1%(bus rear)-1.3%(bus front) under ACH = 5.66 h-1(high bus speed).The TIR of large droplets(i.e., 100 μm/50 μm) is almost independent of ACH, with a peak value(∼3.1%) near the index patient, because over 99.5%/97.0% of droplets deposit locally due to gravity. Moreover, 5 μm droplets can disperse further with the increasing ventilation. However, TIR for 5 μm droplets at ACH = 5.66 h-1 stays relatively small for rear passengers(maximum 0.4%), and is even smaller in the bus middle and front(<0.1%). This study verifies that differing from general rooms, most 5 μm droplets deposit on the route through the long-and-narrow bus space with large-area surfaces(L∼11.4 m). Therefore, tracer gas can only simulate fine droplet with little deposition but cannot replace 5-100 μm droplet dispersion in coach buses.

Modeling the impact of indoor relative humidity on the infection risk of five respiratory airborne viruses

With a modified version of the Wells-Riley model, we simulated the size distribution and dynamics of five airborne viruses (measles, influenza, SARS-CoV-2, human rhinovirus, and adenovirus) emitted from a speaking person in a typical residential setting over a relative humidity (RH) range of 20-80% and air temperature of 20-25 °C. Besides the size transformation of virus-containing droplets due to evaporation, respiratory absorption, and then removal by gravitational settling, the modified model also considered the removal mechanism by ventilation. The trend and magnitude of RH impact depended on the respiratory virus. For rhinovirus and adenovirus humidifying the indoor air from 20/30 to 50% will be increasing the relative infection risk, however, this relative infection risk increase will be negligible for rhinovirus and weak for adenovirus. Humidification will have a potential benefit in decreasing the infection risk only for influenza when there is a large infection risk decrease for humidifying from 20 to 50%. Regardless of the dry solution composition, humidification will overall increase the infection risk via long-range airborne transmission of SARS-CoV-2. Compared to humidification at a constant ventilation rate, increasing the ventilation rate to moderate levels 0.5 → 2.0 h-1 will have a more beneficial infection risk decrease for all viruses except for influenza. Increasing the ventilation rate from low values of 0.5 h-1 to higher levels of 6 h-1 will have a dominating effect on reducing the infection risk regardless of virus type.

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.

Antibacterial Activity of Electrospun Polyacrylonitrile Copper Nanoparticle Nanofibers on Antibiotic Resistant Pathogens and Methicillin Resistant Staphylococcus aureus (MRSA)

Bacteria induced diseases such as community-acquired pneumonia (CAP) are easily transmitted through respiratory droplets expelled from a person’s nose or mouth. It has become increasingly important for researchers to discover materials that can be implemented in in vitro surface contact settings which disrupt bacterial growth and transmission. Copper (Cu) is known to have antibacterial properties and have been used in medical applications. This study investigates the antibacterial properties of polyacrylonitrile (PAN) based nanofibers coated with different concentrations of copper nanoparticles (CuNPs). Different concentrations of copper sulfate (CuSO₄) and polyacrylonitrile (PAN) were mixed with dimethylformamide (DMF) solution, an electrospinning solvent that also acts as a reducing agent for CuSO₄, which forms CuNPs and Cu ions. The resulting colloidal solutions were electrospun into nanofibers, which were then characterized using various analysis techniques. Methicillin-Resistant isolates of Staphylococcus aureus, an infective strain that induces pneumonia, were incubated with cutouts of various nanocomposites using disk diffusion methods on Luria-Bertani (LB) agar to test for the polymers’ antibacterial properties. Herein, we disclose that PAN-CuNP nanofibers have successfully demonstrated antibacterial activity against bacteria that were otherwise resistant to highly effective antibiotics. Our findings reveal that PAN-CuNP nanofibers have the potential to be used on contact surfaces that are at risk of contracting bacterial infections, such as masks, in vivo implants, or surgical intubation.

Airborne transmission of COVID-19 virus in enclosed spaces: An overview of research methods

Since the outbreak of COVID-19 in December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) has spread worldwide. This study summarized the transmission mechanisms of COVID-19 and their main influencing factors, such as airflow patterns, air temperature, relative humidity, and social distancing. The transmission characteristics in existing cases are providing more and more evidence that SARS CoV-2 can be transmitted through the air. This investigation reviewed probabilistic and deterministic research methods, such as the Wells-Riley equation, the dose-response model, the Monte-Carlo model, computational fluid dynamics (CFD) with the Eulerian method, CFD with the Lagrangian method, and the experimental approach, that have been used for studying the airborne transmission mechanism. The Wells-Riley equation and dose-response model are typically used for the assessment of the average infection risk. Only in combination with the Eulerian method or the Lagrangian method can these two methods obtain the spatial distribution of airborne particles' concentration and infection risk. In contrast with the Eulerian and Lagrangian methods, the Monte-Carlo model is suitable for studying the infection risk when the behavior of individuals is highly random. Although researchers tend to use numerical methods to study the airborne transmission mechanism of COVID-19, an experimental approach could often provide stronger evidence to prove the possibility of airborne transmission than a simple numerical model. All in all, the reviewed methods are helpful in the study of the airborne transmission mechanism of COVID-19 and epidemic prevention and control.

A narrative review on the role of temperature and humidity in COVID-19: Transmission, persistence, and epidemiological evidence

Since December 2019, the 2019 coronavirus disease (COVID-19) outbreak has become a global pandemic. Understanding the role of environmental conditions is important in impeding the spread of COVID-19. Given that airborne spread and contact transmission are considered the main pathways for the spread of COVID-19, this narrative review first summarized the role of temperature and humidity in the airborne trajectory of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Meanwhile, we reviewed the persistence of the virus in aerosols and on inert surfaces and summarized how the persistence of SARS-CoV-2 is affected by temperature and humidity. We also examined the existing epidemiological evidence and addressed the limitations of these epidemiological studies. Although uncertainty remains, more evidence may support the idea that high temperature is slightly and negatively associated with COVID-19 growth, while the conclusion for humidity is still conflicting. Nonetheless, the spread of COVID-19 appears to have been controlled primarily by government interventions rather than environmental factors.

Systematic summary and analysis of Chinese HVAC guidelines coping with COVID-19

Heating, Ventilation, and Air-Conditioning (HVAC) system that is almost indispensable service system of modern buildings is recognized as the most important engineering control measure against pandemics. However, the effectiveness of HVAC systems has been questioned on their ability to control airborne transmission. After the outbreak of COVID-19, China has controlled the spread within a relatively short period. Considering the large population, high population density, busy transportation and the overall underdeveloped economy, China's control measures may have some implications to other countries, especially those with limited resources. This paper intends to provide a systematic summary of Chinese ventilation guidelines issued to cope with COVID-19 transmission. The following three aspects are the main focus of these guidelines: (1) general operation and management schemes of various types of HVAC systems, (2) operation and management schemes of HVAC system in typical types of buildings, and (3) design schemes of HVAC system of makeshift hospitals. In addition, some important differences in HVAC guidelines between China and other countries/institutions are identified and compared, and the possible reasons are discussed. Further discussions are made on the following topics, including the required fresh air supply, the extended operation time, the use of auxiliary equipment, the limited capacity of existing systems, and the use of personalized systems.

Investigation of Ventilation Systems to Improve Air Quality in the Occupied Zone in Office Buildings

As a result of COVID-19, many office buildings around the world have downsized their employees, but the comfort parameters in the building had to be kept. The facilities operation rearranged the workstations to keep physical distance and placed plexiglass sheets on the desks for physical protection. A series of measurements have been carried out with workstation set-ups to examine the fresh air rate in the occupied zone. The effect of plexiglass sheets placed on the desks was also examined to see how it changes the airflow pattern in the occupied zone. As the sheets act as a barrier, the primary air does not reach the occupied zone, therefore, the fresh air rate is less. To modify the properties of the ceiling diffusers a new air-ventilation service element was developed. This attachment allows modifying the properties of the ceiling diffusers. Simulations were made at the relevant zones to validate the measurements. Based on design software, the fresh air ratio for a standard ceiling swirl diffuser is 2.46 v% (volume percentage). A numerical model was used to show the fresh air ratio with the system elements for the two different table arrangements, which were 18.3 v% and 21.4 v%, respectively.

Where environmental microbiome meets its host: subway and passenger microbiome relationships

Subways are urban transport systems with high capacity. Every day around the world, there are more than 150 million subway passengers. Since 2013, thousands of microbiome samples from various subways worldwide have been sequenced. Skin bacteria and environmental organisms dominate the subway microbiomes. The literature has revealed common bacterial groups in subway systems; even so, it is possible to identify cities by their microbiome. Low-frequency bacteria are responsible for specific bacterial fingerprints of each subway system. Furthermore, daily subway commuters leave their microbial clouds and interact with other passengers. Microbial exchange is quite fast; the hand microbiome changes within minutes, and after cleaning the handrails, the bacteria are re-established within minutes. To investigate new taxa and metabolic pathways of subway microbial communities, several high-quality metagenomic-assembled genomes (MAG) have been described. Subways are harsh environments unfavorable for microorganism growth. However, recent studies have observed a wide diversity of viable and metabolically active bacteria. Understanding which bacteria are living, dormant, or dead allows us to propose realistic ecological interactions. Questions regarding the relationship between humans and the subway microbiome, particularly the microbiome effects on personal and public health, remain unanswered. This review summarizes our knowledge of subway microbiomes and their relationship with passenger microbiomes.

Sneezing Aerosol Transport in an Indoor Farmers’ Market

The transportation and surface deposition of aerosols from sneezing in a small indoor farmers’ market are studied numerically. The effects of numbers and locations of the entrances and exits of the market are discussed under the condition of natural convection. The results indicate that aerosols leave the indoor environment more quickly when two doors are designed face to face on the walls perpendicular to the natural wind direction compared to other natural ventilation strategies. The concentrations of aerosols accumulated on the surfaces of the stalls and human bodies inside the market are also lower. In this case, the risk of contacting the virus is relatively low among susceptible individuals in the indoor farmers’ markets. Moreover, opening more doors on the walls parallel to the natural wind direction is not beneficial for the fast exhaust of aerosols.

The source control effect of personal protection equipment and physical barrier on short-range airborne transmission

In order to control the spread of Covid-19, authorities provide various prevention guidelines and recommendations for health workers and the public. Personal protection equipment (PPE) and physical barrier are the most widely applied prevention measures in practice due to their affordability and ease of implementation. This study aims to investigate the effect of PPE and physical barriers on mitigating the short-range airborne transmission between two people in a ventilated environment. Four types of PPE (surgical mask, two types of face shield, and mouth visor), and two different sizes of the physical barrier were tested in a controlled environment with two life-size breathing thermal manikins. The PPE was worn by the source manikin to test the efficiency of source control. The measurement results revealed that the principles of PPE on preventing short-range droplet and airborne transmission are different. Instead of filtering the fine droplet nuclei, they mainly redirect the virus-laden exhalation jet and avoid the exhaled flow entering the target's inhalation region. Physical barriers can block the spreading of droplet nuclei and create a good micro environment at short distances between persons. However, special attention should be paid to arranging the physical barrier and operating the ventilation system to avoid the stagnant zone where the contaminant accumulates.

Beyond well-mixed: A simple probabilistic model of airborne disease transmission in indoor spaces

We develop a simple model for assessing risk of airborne disease transmission that accounts for non-uniform mixing in indoor spaces and is compatible with existing epidemiological models. A database containing 174 high-resolution simulations of airflow in classrooms, lecture halls, and buses is generated and used to quantify the spatial distribution of expiratory droplet nuclei for a wide range of ventilation rates, exposure times, and room configurations. Imperfect mixing due to obstructions, buoyancy, and turbulent dispersion results in concentration fields with significant variance. The spatial non-uniformity is found to be accurately described by a shifted lognormal distribution. A well-mixed mass balance model is used to predict the mean, and the standard deviation is parameterized based on ventilation rate and room geometry. When employed in a dose-response function risk model, infection probability can be estimated considering spatial heterogeneity that contributes to both short- and long-range transmission.

Modeling the factors that influence exposure to SARS-CoV-2 on a subway train carriage

We propose the Transmission of Virus in Carriages (TVC) model, a computational model which simulates the potential exposure to SARS-CoV-2 for passengers traveling in a subway rail system train. This model considers exposure through three different routes: fomites via contact with contaminated surfaces; close-range exposure, which accounts for aerosol and droplet transmission within 2 m of the infectious source; and airborne exposure via small aerosols which does not rely on being within 2 m distance from the infectious source. Simulations are based on typical subway parameters and the aim of the study is to consider the relative effect of environmental and behavioral factors including prevalence of the virus in the population, number of people traveling, ventilation rate, and mask wearing as well as the effect of model assumptions such as emission rates. Results simulate generally low exposures in most of the scenarios considered, especially under low virus prevalence. Social distancing through reduced loading and high mask-wearing adherence is predicted to have a noticeable effect on reducing exposure through all routes. The highest predicted doses happen through close-range exposure, while the fomite route cannot be neglected; exposure through both routes relies on infrequent events involving relatively few individuals. Simulated exposure through the airborne route is more homogeneous across passengers, but is generally lower due to the typically short duration of the trips, mask wearing, and the high ventilation rate within the carriage. The infection risk resulting from exposure is challenging to estimate as it will be influenced by factors such as virus variant and vaccination rates.

Breathing zone and exhaled air re-inhalation rate under transient conditions assessed with a computer-simulated person

The breathing zone of an individual indoors is usually defined as a finite region steadily formed in front of a face. Assuming the steady formation of the breathing zone, we propose a procedure for quantitatively identifying a breathing zone formed in front of a human face in the transient condition. This assumption is reasonable considering that the ventilation time scale of human respiration is sufficiently short compared to the ventilation time scale of a room. We used steady-state computational fluid dynamics (CFD) and a computationally simulated person (CSP). We present the probabilistic size of the breathing zone for various postures and breathing conditions. By analyzing unsteady inhalation and exhalation airflow characteristics via a CSP with a respiratory system, we also estimated the direct re-inhalation rate of the exhaled air. The results can be used for developing methods to control the long-term and low-contaminant concentration exposures.

Investigation on the evaporation and dispersion of human respiratory droplets with COVID-19 virus

On March 11, 2020, COVID-19 was declared as a pandemic by World Health Organization (WHO). Effective prevention is indispensable for defeating the ongoing COVID-19 pandemic. The evaporation and diffusion characteristics of the droplet in the air are the critical factors for the virus transmission by droplets. To better understand transmission routes of COVID-19 through respiratory droplets, a new evaporation and dispersion model for respiratory droplets is proposed to estimate droplet lifetime and the size of spreading zone in air. The importance of respiratory activities and environmental factors on the transmission of respiratory viruses are further discussed. The predictive results demonstrate initial particle size, ambient temperature and relative humidity all have significant effect on the survival time and infection distance of respiratory droplets. Decreasing droplet initial size always shortens the lifetime and the transmission distance of respiratory droplets. The 100 μm droplets expelled by talking or coughing can be carried more than 2 m away. Increasing ambient temperature and decreasing ambient humidity can effectively reduce the lifetime and propagation distance of respiratory droplets, thus reducing the risk of viral infection. These findings could contribute to developing effective prevention measures for controlling infectious disease transmission via droplets.