Influence of pulmonary ventilation rate and breathing cycle period on the risk of cross-infection

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.

Quantitatively Visualizing Airborne Disease Transmission Risks of Different Exhalation Activities through CO2 Imaging

Aerosol transmission has played a leading role in COVID-19 pandemic. However, there is still a poor understanding about how it is transmitted. This work was designed to study the exhaled breath flow dynamics and transmission risks under different exhaling modes. Using an infrared photography device, exhaled flow characteristics of different breathing activities, such as deep breathing, dry coughing, and laughing, together with the roles of mouth and nose were characterized by imaging CO2 flow morphologies. Both mouth and nose played an important role in the disease transmission though in the downward direction for the nose. In contrast to the trajectory commonly modeled, the exhaled airflows appeared with turbulent entrainments and obvious irregular movements, particularly the exhalations involving mouth were directed horizontal and had a higher propagation capacity and transmission risk. While the cumulative risk was high for deep breathing, those transient ones from dry coughing, yawning, and laughing were also shown to be significant. Various protective measures including masks, canteen table shields, and wearable devices were visually demonstrated to be effective for altering the exhaled flow directions. This work is useful to understanding the risk of aerosol infection and guiding the formulation of its prevention and control strategies. Experimental data also provide important information for refining model boundary conditions.

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.

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

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

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.

CFD modeling of airborne pathogen transmission of COVID-19 in confined spaces under different ventilation strategies

Airborne transmission is an important route of spread of viral diseases (e.g., COVID-19) inside the confined spaces. In this respect, computational fluid dynamics (CFD) emerged as a reliable and fast tool to understand the complex flow patterns in such spaces. Most of the recent studies, nonetheless, focused on the spatial distribution of airborne pathogens to identify the infection probability without considering the exposure time. This research proposes a framework to evaluate the infection probability related to both spatial and temporal parameters. A validated Eulerian-Lagrangian CFD model of exhaled droplets is first developed and then evaluated with an office case study impacted by different ventilation strategies (i.e., cross- (CV), single- (SV), mechanical- (MV) and no-ventilation (NV)). CFD results were analyzed in a bespoke code to calculate the tempo-spatial distribution of accumulated airborne pathogens. Furthermore, two indices of local and general infection risks were used to evaluate the infection probability of the ventilation scenarios. The results suggest that SV has the highest infection probability while SV and NO result in higher dispersions of airborne pathogens inside the room. Eventually, the time history of indices reveals that the efficiency of CV and MV can be poor in certain regions of the room.

Close proximity risk assessment for SARS-CoV-2 infection

Although the interpersonal distance represents an important parameter affecting the risk of infection due to respiratory viruses, the mechanism of exposure to exhaled droplets remains insufficiently characterized. In this study, an integrated risk assessment is presented for SARS-CoV-2 close proximity exposure between a speaking infectious subject and a susceptible subject. It is based on a three-dimensional transient numerical model for the description of exhaled droplet spread once emitted by a speaking person, coupled with a recently proposed SARS-CoV-2 emission approach. Particle image velocimetry measurements were conducted to validate the numerical model. The contribution of the large droplets to the risk is barely noticeable only for distances well below 0.6 m, whereas it drops to zero for greater distances where it depends only on airborne droplets. In particular, for short exposures (10 s) a minimum safety distance of 0.75 m should be maintained to lower the risk below 0.1%; for exposures of 1 and 15 min this distance increases to about 1.1 and 1.5 m, respectively. Based on the interpersonal distances across countries reported as a function of interacting individuals, cultural differences, and environmental and sociopsychological factors, the approach presented here revealed that, in addition to intimate and personal distances, particular attention must be paid to exposures longer than 1 min within social distances (of about 1 m).

Dismantling myths on the airborne transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)

The coronavirus disease 2019 (COVID-19) pandemic has caused untold disruption throughout the world. Understanding the mechanisms for transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is key to preventing further spread, but there is confusion over the meaning of ‘airborne’ whenever transmission is discussed. Scientific ambivalence originates from evidence published many years ago which has generated mythological beliefs that obscure current thinking. This article collates and explores some of the most commonly held dogmas on airborne transmission in order to stimulate revision of the science in the light of current evidence. Six ‘myths’ are presented, explained and ultimately refuted on the basis of recently published papers and expert opinion from previous work related to similar viruses. There is little doubt that SARS-CoV-2 is transmitted via a range of airborne particle sizes subject to all the usual ventilation parameters and human behaviour. Experts from specialties encompassing aerosol studies, ventilation, engineering, physics, virology and clinical medicine have joined together to produce this review to consolidate the evidence for airborne transmission mechanisms, and offer justification for modern strategies for prevention and control of COVID-19 in health care and the community.

Evaluation of an innovative pediatric isolation (PI) bed using fluid dynamics simulation and aerosol isolation efficacy

Airborne transmission is an important mechanism of spread for both viruses and bacteria in hospitals, with nosocomial infections putting a great burden on public health. In this study, we designed and manufactured a bed for pediatric clinic consultation rooms providing air isolation to protect patients and medical personnel from pathogen transmission. The pediatric isolation bed has several primary efficiency filters and a high-efficiency particulate air filter in the bedside unit. The air circulation between inlet and outlet forms negative pressure to remove the patient's exhaled air timeously and effectively. A computational fluid dynamics model was used to calculate the speed of the airflow and the angle of sampler. Following this, we conducted purification experiments using cigarette smoke, Staphylococcus albus (S. albus) and human adenovirus type 5 (HAdV-5) to demonstrate the isolation efficacy. The results showed that the patient's head should be placed as close to the air inlet hood as possible, and an air intake wind speed of 0.86 m/s was effective. The isolation efficacy of the pediatric isolation bed was demonstrated by computational fluid dynamics technology. The isolation efficiency against cigarette smoke exceeded 91.8%, and against S. albus was greater than 99.8%, while the isolation efficiency against HAdV-5 was 100%. The pediatric isolation bed could be used where isolation wards are unavailable, such as in intensive care units and primary clinical settings, to control hospital acquired infections.

Intermittent occupancy combined with ventilation: An efficient strategy for the reduction of airborne transmission indoors

It is important that efficient measures to reduce the airborne transmission of respiratory infectious diseases (including COVID-19) should be formulated as soon as possible to ensure a safe easing of lockdown. Ventilation has been widely recognized as an efficient engineering control measure for airborne transmission. Room ventilation with an increased supply of clean outdoor air could dilute the expiratory airborne aerosols to a lower concentration level. However, sufficient increase is beyond the capacity of most of the existing mechanical ventilation systems that were designed to be energy efficient under non-pandemic conditions. We propose an improved control strategy based on source control, which would be achieved by implementing intermittent breaks in room occupancy, specifically that all occupants should leave the room periodically and the room occupancy time should be reduced as much as possible. Under the assumption of good mixing of clean outdoor supply air with room air, the evolution of the concentration in the room of aerosols exhaled by infected person(s) is predicted. The risk of airborne cross-infection is then evaluated by calculating the time-averaged intake fraction. The effectiveness of the strategy is demonstrated for a case study of a typical classroom. This strategy, together with other control measures such as continuous supply of maximum clean air, distancing, face-to-back layout of workstations and reducing activities that increase aerosol generation (e.g., loudly talking and singing), is applicable in classrooms, offices, meeting rooms, conference rooms, etc.