SARS-CoV-2 airborne infection probability estimated by using indoor carbon dioxide.

Airborne transmission is one of the main routes of SARS-CoV-2 spread. It is important to determine the circumstances under which the risk of airborne transmission is increased as well as the effective strategy to reduce such risk. This study aimed to develop a modified version of the Wells-Riley model with indoor CO2 to estimate the probability of airborne transmission of SARS-CoV-2 Omicron strains with a CO2 monitor and to evaluate the validity of this model in actual clinical practices. We used the model in three suspected cases of airborne transmission presented to our hospital to confirm its validity. Next, we estimated the required indoor CO2 concentration at which R0 does not exceed 1 based on the model. The estimated R0 (R0, basic reproduction number) based on the model in each case were 3.19 in three out of five infected patients in an outpatient room, 2.00 in two out of three infected patients in the ward, and 0.191 in none of the five infected patients in another outpatient room. This indicated that our model can estimate R0 with an acceptable accuracy. In a typical outpatient setting, the required indoor CO2 concentration at which R0 does not exceed 1 is below 620 ppm with no mask, 1000 ppm with a surgical mask and 16000 ppm with an N95 mask. In a typical inpatient setting, on the other hand, the required indoor CO2 concentration is below 540 ppm with no mask, 770 ppm with a surgical mask, and 8200 ppm with an N95 mask. These findings facilitate the establishment of a strategy for preventing airborne transmission in hospitals. This study is unique in that it suggests the development of an airborne transmission model with indoor CO2 and application of the model to actual clinical practice. Organizations and individuals can efficiently recognize the risk of SARS-CoV-2 airborne transmission in a room and thus take preventive measures such as maintaining good ventilation, wearing masks, or shortening the exposure time to an infected individual by simply using a CO2 monitor.

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.

Predicting the infection probability distribution due to airborne and droplet transmission

In this study, a method was proposed to predict the infection probability distribution rather than the room-averaged value. The infection probability by airborne transmission was predicted based on the CO2 concentration. The infection probability by droplet transmission was predicted based on occupant position information. Applying the proposed method to an actual office confirmed that it could be used for quantitatively predicting the infection probability by integrating the ventilation efficiency and distance between occupants. The infection probability by airborne transmission was relatively high in a zone where the amount of outdoor air supply was relatively small. The infection probability by droplet transmission varied with the position of the occupants. The ability of the proposed method to analyze the relative effectiveness of countermeasures for airborne transmission and droplet transmission was verified in this study. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Measurement of Ventilation Rate and Evaluation of Infection Risk in a Classroom

To quantitatively evaluate the effect of increasing ventilation using the immediately practicable method on infection risk, the ventilation rate in a classroom was measured by the concentration decay method using CO2. The measured value was then substituted into the Wells-Riley model to evaluate aerosol infection risk in steady and non-steady states. In the classroom, the air change rate per hour (ACH) ranged from 3.1 to 10.2, and the local mean age of air tended to be larger near the outlet. It was also shown that opening the windows increased the ventilation rate the most, resulting in a more evenly distributed local mean age of air. We also showed that the aerosol infection risk in the classroom could be significantly reduced by increasing ventilation, suppressing vocalization, and wearing a mask, compared to some outbreaks of COVID-19. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Experimental study on the effect of 4-way active chilled beam ventilation system on airborne infection risk

With the global outbreak of infectious respiratory diseases COVID-19, it is critical to evaluate the indoor airborne infection risk. The ventilation strategies and air distribution methods may affect indoor cross-infection significantly. This study aims to evaluate the effect of 4-way active chilled beam ventilation system on airborne infection risk. An experimental study has been conducted in a test chamber to investigate airborne transmission in an office room with two different heat load conditions and two chilled beam types. Tracer gas technique was used to simulate the exhaled droplet nuclei from the infected person and the photoacoustic gas analyser (Gasera One) was used to monitor the concentration of SF6. The revised Wells-Riley model was used to calculate the infection probability with both spatial and temporal resolutions. One of the occupants was an infector, and the influence of three factors were explored, including the infector's location, air distribution patterns, and heat load levels. To evaluate the dynamics of airborne exposure, real-time and average exposure indices were proposed. The experimental results illustrated that the airborne infection risk increased linearly within 30 min of the exposure time, and then keep a constant state. Under the same heat load conditions, 2 pcs of 1200 chilled beam system directed the particles in the occupied zone to the outlet effectively and reduced the infection rate of personnel in occupied zone. The location of the infector had a significant impact on the infection probability for the active chilled beam ventilation system. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Assessment of respiratory disease infection risk and natural ventilation intervention countermeasures in teaching spaces: A campus case study

The risk of indoor respiratory disease transmission can be significantly reduced through interventions that target the built environment. Several studies have successfully developed theoretical models to calculate the effects of built environment parameters on infection rates. However, current studies have mainly focused on calculating infection rate values and comparing pre- and post-optimization values, lacking a discussion of safe baseline values for infection rates with risk class classification. The purpose of this paper is to explore the design of interventions in the built environment to improve the ability of buildings to prevent virus transmission, with a university campus as an example. The study integrates the Wells-Riley model and basic reproduction number to identify teaching spaces with high infection risk on campus and proposes targeted intervention countermeasures based on the analysis of critical parameters. The results showed that teaching buildings with a grid layout pattern had a higher potential risk of infection under natural ventilation. By a diversity of building environment interventions designed, the internal airflow field of classrooms can be effectively organized, and the indoor virus concentration can be reduced. We can find that after optimizing the building mentioned above and environment intervention countermeasures, the maximum indoor virus infection probability can be reduced by 22.88%, and the basic reproduction number can be reduced by 25.98%, finally reaching a safe level of less than 1.0. In this paper, we support university campuses' respiratory disease prevention and control programs by constructing theoretical models and developing parametric platforms. © 2023 Elsevier Ltd

Animal experiments on respiratory viruses and analogous studies of infection factors for interpersonal transmission.

Air pollution caused by SARS-CoV-2 and other viruses in human settlements will have a great impact on human health, but also a great risk of transmission. The transmission power of the virus can be represented by quanta number in the Wells-Riley model. In order to solve the problem of different dynamic transmission scenarios, only a single influencing factor is considered when predicting the infection rate, which leads to large differences in quanta calculated in the same space. In this paper, an analog model is established to define the indoor air cleaning index RL and the space ratio parameter. Based on infection data analysis and rule summary in animal experiments, factors affecting quanta in interpersonal communication were explored. Finally, by analogy, the factors affecting person-to-person transmission mainly include viral load of infected person, distance between individuals, etc., the more severe the symptoms, the closer the number of days of illness to the peak, and the closer the distance to the quanta. In summary, there are many factors that affect the infection rate of susceptible people in the human settlement environment. This study provides reference indicators for environmental governance under the COVID-19 epidemic, provides reference opinions for healthy interpersonal communication and human behavior, and provides some reference for accurately judging the trend of epidemic spread and responding to the epidemic.

Evaluation of indoor environmental quality, personal cumulative exposure dose, and aerosol transmission risk levels inside urban buses in Dalian, China.

The transmission of pollutants in buses has an important impact on personal exposure to airborne particles and spread of the COVID-19 epidemic in enclosed spaces. We conducted the following real-time field measurements inside buses: CO2, airborne particle concentration, temperature, and relative humidity data during peak and off-peak hours in spring and autumn. Correlation analysis was adopted to evaluate the dominant factors influencing CO2 and particle mass concentrations in the vehicle. The cumulative personal exposure dose to particulate matter and reproduction number were calculated for passengers on a one-way trip. The results showed the in-cabin CO2 concentrations, with 22.11% and 21.27% of the total time exceeding 1000 ppm in spring and autumn respectively. In-cabin PM2.5 mass concentration exceeded 35 µm/m3 by 57.35% and 86.42% in spring and autumn, respectively. CO2 concentration and the cumulative number of passengers were approximately linearly correlated in both seasons, with R value up to 0.896. The cumulative number of passengers had the most impact on PM2.5 mass concentration among tested parameters. The cumulative personal exposure dose to PM2.5 during a one-way trip in autumn was up to 43.13 µg. The average reproductive number throughout the one-way trip was 0.26; it was 0.57 under the assumed extreme environment. The results of this study provide an important basic theoretical guidance for the optimization of ventilation system design and operation strategies aimed at reducing multi-pollutant integrated health exposure and airborne particle infection (such as SARS-CoV-2) risks.

Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects.

The Wells-Riley model invokes human physiological and engineering parameters to successfully treat airborne transmission of infectious diseases. Applications of this model would have high potentiality on evaluating policy actions and interventions intended to improve public safety efforts on preventing the spread of COVID-19 in an enclosed space. Here, we constructed the interaction relationships among basic reproduction number (R0) - exposure time - indoor population number by using the Wells-Riley model to provide a robust means to assist in planning containment efforts. We quantified SARS-CoV-2 changes in a case study of two Wuhan (Fangcang and Renmin) hospitals. We conducted similar approach to develop control measures in various hospital functional units by taking all accountable factors. We showed that inhalation rates of individuals proved crucial for influencing the transmissibility of SARS-CoV-2, followed by air supply rate and exposure time. We suggest a minimum air change per hour (ACH) of 7 h-1 would be at least appropriate with current room volume requirements in healthcare buildings when indoor population number is < 10 and exposure time is < 1 h with one infector and low activity levels being considered. However, higher ACH (> 16 h-1) with optimal arranged-exposure time/people and high-efficiency air filters would be suggested if more infectors or higher activity levels are presented. Our models lay out a practical metric for evaluating the efficacy of control measures on COVID-19 infection in built environments. Our case studies further indicate that the Wells-Riley model provides a predictive and mechanistic basis for empirical COVID-19 impact reduction planning and gives a framework to treat highly transmissible but mechanically heterogeneous airborne SARS-CoV-2.

Evaluation of infection probability of Covid-19 in different types of airliner cabins.

According to the World Health Organization (https://covid19.who.int/), more than 651 million people have been infected by COVID-19, and more than 6.6 million of them have died. COVID-19 has spread to almost every country in the world because of air travel. Cases of COVID-19 transmission from an index patient to fellow passengers in commercial airplanes have been widely reported. This investigation used computational fluid dynamics (CFD) to simulate airflow and COVID-19 virus (SARS-CoV-2) transport in a variety of airliner cabins. The cabins studied were economy-class with 2-2, 3-3, 2-3-2, and 3-3-3 seat configurations, respectively. The CFD results were validated by using experimental data from a seven-row cabin mockup with a 3-3 seat configuration. This study used the Wells-Riley model to estimate the probability of infection with SARS-CoV-2. The results show that CFD can predict airflow and virus transmission with acceptable accuracy. With an assumed flight time of 4 h, the infection probability was almost the same among the different cabins, except that the 3-3-3 configuration had a lower risk because of its airflow pattern. Flying time was the most important parameter for causing the infection, while cabin type also played a role. Without mask wearing by the passengers and the index patient, the infection probability could be 8% for a 10-h, long-haul flight, such as a twin-aisle air cabin with 3-3-3 seat configuration.

Computational fluid dynamics simulation of airborne COVID transmission in urban bus with different HVAC configurations

The HVAC systems in closed buses promote high particle spread. Lagrangian particle tracking simulations were carried out to evaluate airborne COVID transmission through droplets emitted by sneezing while Eulerian simulations were performed to account for the spread of aerosols emitted by breathing. The position of passengers as well as the effect of three HVAC configurations were evaluated. On one hand, it was concluded that large droplets can travel more than 3 m without being significantly affected by the inflow conditions, but small droplets are easily dispersed by the airflow, and many of them are captured by the HVAC systems. On the other hand, the HVAC systems quickly spreads aerosols along the whole of the bus, increasing the average risk for all passengers, but sensibly reducing the high local risks observed under motionless inflow conditions. The transmission risk was calculated by applying the Wells-Riley model, concluding that the transmission risk for a 20-min trip could remain below 0.5% if HVAC configurations with many inlet/outlet vents are implemented, and the passengers remain in silence and wear face masks.

A NUMERICAL SET-UP FOR THE SIMULATION OF INFECTION PROBABILITY FROM SARS- COV-2 IN PUBLIC TRANSPORT VEHICLES

In this work, a numerical framework aimed at simulating the transport of contaminants and infectious agents within a closed domain is presented. The method employs mature CFD algorithms to calculate air fields with reasonable computational costs. The main objective is to give fast response to stakeholders about air quality indicators in the design phase of HVAC systems. A discussion regarding the size and characteristics of different contaminants is proposed, highlighting the most appropriate methods and coefficients needed to simulate their transport. Next, the methodology employed to evaluate the risk of infection is presented. The numerical set-up, based on the buoyantBoussinesqPimpleFoam solver in OpenFOAM, was tuned by simulating the well-known case of the heated floor cavity, providing accurate results. Hence, the case study of a transport vehicle of generic shape is presented, in order to show possible results in terms of air-age distribution, PM2.5 distribution, and global infection risk matrix. © 2022, Scipedia S.L. All rights reserved.

Computational fluid dynamics simulation of airborne COVID transmission in urban bus with different HVAC configurations

The HVAC systems in closed buses promote high particle spread. Lagrangian particle tracking simulations were carried out to evaluate airborne COVID transmission through droplets emitted by sneezing while Eulerian simulations were performed to account for the spread of aerosols emitted by breathing. The position of passengers as well as the effect of three HVAC configurations were evaluated. On one hand, it was concluded that large droplets can travel more than 3 m without being significantly affected by the inflow conditions, but small droplets are easily dispersed by the airflow, and many of them are captured by the HVAC systems. On the other hand, the HVAC systems quickly spreads aerosols along the whole of the bus, increasing the average risk for all passengers, but sensibly reducing the high local risks observed under motionless inflow conditions. The transmission risk was calculated by applying the Wells-Riley model, concluding that the transmission risk for a 20-min trip could remain below 0.5% if HVAC configurations with many inlet/outlet vents are implemented, and the passengers remain in silence and wear face masks. [ FROM AUTHOR]

A spatiotemporal assessment of occupants' infection risks in a multi-occupants space using modified Wells-Riley model.

Escalating demands of assessing airborne disease infection risks had been awakened from ongoing pandemics. An inhalation index linked to biomedical characteristics of pathogens (e.g. TCID 50 for coronavirus delta variant) was proposed to quantify human uptake dose. A modified Wells-Riley risk-assessment framework was then developed with enhanced capability of integrating biological and spatiotemporal features of infectious pathogens into assessment. The instantaneous transport characteristics of pathogens were traced by Eulerian-Lagrangian method. Droplets released via speaking and coughing in a conference room with three ventilation strategies were studied to assess occupants' infection risks using this framework. Outcomes revealed that speaking droplets could travel with less distance (0.5 m) than coughing droplets (1 m) due to the frequent interaction between speaking flow and thermal plume. Quantified analysis of inhalation index revealed a higher inhalation possibility of droplets with nuclei size smaller than 5 µ m , and this cut-off size was found sensitive to ventilation. With only 60-second exposure, occupants in the near-field of host started to have considerable infection risks (approximately 20%). This risk was found minimising over distance exponentially. This modified framework demonstrated the systematic analysis of airborne transmission, from quantifying particle inhalation possibility, targeting specific disease's TCID 50 , to ultimate evaluation of infection risks.

The Effects of Intervention Strategies for COVID-19 Transmission Control on Campus Activity

University is one of the most likely environments for the cluster infection due to the long-time close contact in house and frequent communication. It is critical to understand the transmission risk of COVID-19 under various scenario, especially during public health emergency. Taking the Tsinghua university's anniversary as a representative case, a set of prevention and control strategies are established and investigated. In the case study, an alumni group coming from out of campus is investigated whose activities and routes are designed based on the previous anniversary schedule. The social closeness indicator is introduced into the Wells-Riley model to consider the factor of contact frequency. Based on the anniversary scenario, this study predicts the number of the infected people in each exposure indoor location (including classroom, dining hall, meeting room and so on) and evaluates the effects of different intervention measures on reducing infection risk using the modified Wells-Riley model, such as ventilation, social distancing and wearing mask. The results demonstrate that when applying the intervention measure individually, increasing ventilation rate is found to be the most effective, whereas the efficiency of increased ventilation on reducing infection cases decreases with the increase of the ventilation rate. To better prevent COVID-19 transmission, the combined intervention measures are necessary to be taken, which show the similar effectiveness on the reduction of infected cases under different initial infector proportion. The results provide the insights into the infection risk on university campus when dealing with public health emergency and can guide university to formulate effective operational strategies to control the spread of COVID-19. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

New dose-response model and SARS-CoV-2 quanta emission rates for calculating the long-range airborne infection risk.

Predictive models for airborne infection risk have been extensively used during the pandemic, but there is yet still no consensus on a common approach, which may create misinterpretation of results among public health experts and engineers designing building ventilation. In this study we applied the latest data on viral load, aerosol droplet sizes and removal mechanisms to improve the Wells Riley model by introducing the following novelties i) a new model to calculate the total volume of respiratory fluid exhaled per unit time ii) developing a novel viral dose-based generation rate model for dehydrated droplets after expiration iii) deriving a novel quanta-RNA relationship for various strains of SARS-CoV-2 iv) proposing a method to account for the incomplete mixing conditions. These new approaches considerably changed previous estimates and allowed to determine more accurate average quanta emission rates including omicron variant. These quanta values for the original strain of 0.13 and 3.8 quanta/h for breathing and speaking and the virus variant multipliers may be used for simple hand calculations of probability of infection or with developed model operating with six size ranges of aerosol droplets to calculate the effect of ventilation and other removal mechanisms. The model developed is made available as an open-source tool.

Modeling the effects of vaccination, nucleic acid testing, and face mask wearing interventions against COVID-19 in large sports events.

The transmission of SARS-CoV-2 leads to devastating COVID-19 infections around the world, which has affected both human health and the development of industries dependent on social gatherings. Sports events are one of the subgroups facing great challenges. The uncertainty of COVID-19 transmission in large-scale sports events is a great barrier to decision-making with regard to reopening auditoriums. Policymakers and health experts are trying to figure out better policies to balance audience experiences and COVID-19 infection control. In this study, we employed the generalized SEIR model in conjunction with the Wells-Riley model to estimate the effects of vaccination, nucleic acid testing, and face mask wearing on audience infection control during the 2021 Chinese Football Association Super League from 20 April to 5 August. The generalized SEIR modeling showed that if the general population were vaccinated by inactive vaccines at an efficiency of 0.78, the total number of infectious people during this time period would decrease from 43,455 to 6,417. We assumed that the general population had the same odds ratio of entering the sports stadiums and becoming the audience. Their infection probabilities in the stadium were further estimated by the Wells-Riley model. The results showed that if all of the 30,000 seats in the stadium were filled by the audience, 371 audience members would have become infected during the 116 football games in the 2021 season. The independent use of vaccination and nucleic acid testing would have decreased this number to 79 and 118, respectively. The combined use of nucleic acid testing and vaccination or face mask wearing would have decreased this number to 14 and 34, respectively. The combined use of all three strategies could have further decreased this number to 0. According to the modeling results, policymakers can consider the combined use of vaccination, nucleic acid testing, and face mask wearing to protect audiences from infection when holding sports events, which could create a balance between audience experiences and COVID-19 infection control.

Bioaerosol distribution characteristics and potential SARS-CoV-2 infection risk in a multi-compartment dental clinic.

Dental clinics have a potential risk of infection, particularly during the COVID-19 pandemic. Multi-compartment dental clinics are widely used in general hospitals and independent clinics. This study utilised computational fluid dynamics to investigate the bioaerosol distribution characteristics in a multi-compartment dental clinic through spatiotemporal distribution, working area time-varying concentrations, and key surface deposition. The infection probability of SARS-CoV-2 for the dental staff and patients was calculated using the Wells-Riley model. In addition, the accuracy of the numerical model was verified by field measurements of aerosol concentrations performed during a clinical ultrasonic scaling procedure. The results showed that bioaerosols were mainly distributed in the compartments where the patients were treated. The average infection probability was 3.8% for dental staff. The average deposition number per unit area of the treatment chair and table are 28729 pcs/m2 and 7945 pcs/m2, respectively, which creates a possible contact transmission risk. Moreover, there was a certain cross-infection risk in adjacent compartments, and the average infection probability for patients was 0.84%. The bioaerosol concentrations of the working area in each compartment 30 min post-treatment were reduced to 0.07% of those during treatment, and the infection probability was <0.05%. The results will contribute to an in-depth understanding of the infection risk in multi-compartment dental clinics, forming feasible suggestions for management to efficiently support epidemic prevention and control in dental clinics.

Zonal modeling of air distribution impact on the long-range airborne transmission risk of SARS-CoV-2.

A widely used analytical model to quantitatively assess airborne infection risk is the Wells-Riley model which is limited to complete air mixing in a single zone. However, this assumption tends not to be feasible (or reality) for many situations. This study aimed to extend the Wells-Riley model so that the infection risk can be calculated in spaces where complete mixing is not present. Some more advanced ventilation concepts create either two horizontally divided air zones in spaces as displacement ventilation or the space may be divided into two vertical zones by downward plane jet as in protective-zone ventilation systems. This is done by evaluating the time-dependent distribution of infectious quanta in each zone and by solving the coupled system of differential equations based on the zonal quanta concentrations. This model introduces a novel approach by estimating the interzonal mixing factor based on previous experimental data for three types of ventilation systems: incomplete mixing ventilation, displacement ventilation, and protective zone ventilation. The modeling approach is applied to a room with one infected and one susceptible person present. The results show that using the Wells-Riley model based on the assumption of completely air mixing may considerably overestimate or underestimate the long-range airborne infection risk in rooms where air distribution is different than complete mixing, such as displacement ventilation, protected zone ventilation, warm air supplied from the ceiling, etc. Therefore, in spaces with non-uniform air distribution, a zonal modeling approach should be preferred in analytical models compared to the conventional single-zone Wells-Riley models when assessing long-range airborne transmission risk of infectious respiratory diseases.

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.