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

VLP-based model for the study of airborne viral pathogens

The recent COVID-19 pandemic has underscored the danger of airborne viral pathogens. The lack of model systems to study airborne pathogens limits the understanding of airborne pathogen distribution as well as potential surveillance and mitigation strategies. In this work, we develop a novel model system to study airborne pathogens using virus-like particles (VLPs). Specifically, we demonstrate the ability to aerosolize VLP and detect and quantify aerosolized VLP RNA by reverse transcription-loop-mediated isothermal amplification in real-time fluorescent and colorimetric assays. Importantly, the VLP model presents many advantages for the study of airborne viral pathogens: (i) similarity in size and surface components; (ii) ease of generation and noninfectious nature enabling the study of biosafety level 3 and biosafety level 4 viruses; (iii) facile characterization of aerosolization parameters; (iv) ability to adapt the system to other viral envelope proteins, including those of newly discovered pathogens and mutant variants; and (v) the ability to introduce viral sequences to develop nucleic acid amplification assays.

IMPORTANCE

The study and detection of airborne pathogens are hampered by the lack of appropriate model systems. In this work, we demonstrate that noninfectious virus-like particles (VLPs) represent attractive models to study airborne viral pathogens. Specifically, VLPs are readily prepared, are similar in size and composition to infectious viruses, and are amenable to highly sensitive nucleic acid amplification techniques.

Evaluating infection risks in buses based on passengers' dynamic temporal and typical spatial scenarios: A case study of COVID-19

Conventional buses, as an indispensable part of the urban public transport system, impose cross-infection risks on passengers. To assess differential risks due to dynamic staying durations and locations, this study considered four spatial distributions (i = 1-4) and six temporal scenarios (j = 1-6) of buses. Based on field measurements and a risk assessment approach combining both short-range and room-scale effects, risks are evaluated properly. The results showed that temporal asynchrony between infected and susceptible individuals significantly affects disease transmission rates. The Control Case assumes that infected and susceptible individuals enter and leave synchronously. However, ignoring temporal asynchrony scenarios, i.e., the Control Case, resulted in overestimation (+30.7 % to +99.6 %) or underestimation (-15.2 % to -69.9 %) of the actual risk. Moreover, the relative difference ratios of room-scale risks between the Control Case and five temporal scenarios are impacted by ventilation. Short-range risk exists only if infected and susceptible individuals have temporal overlap on the bus. Considering temporal and spatial asynchrony, a more realistic total reproduction number (R) can be obtained. Subsequently, the total R was assessed under five temporal scenarios. On average, for the Control Case, the total R was estimated to be +27.3 % higher than j = 1, -9.3 % lower than j = 2, +12.8 % higher than j = 3, +33.0 % lower than j = 4, and + 77.6 % higher than j = 5. This implies the need for a combination of active prevention and real-time risk monitoring to enable rigid travel demand and control the spread of the epidemic.

The Wells-Riley model revisited: Randomness, heterogeneity, and transient behaviours

The Wells-Riley model has been widely used to estimate airborne infection risk, typically from a deterministic point of view (i.e., focusing on the average number of infections) or in terms of a per capita probability of infection. Some of its main limitations relate to considering well-mixed air, steady-state concentration of pathogen in the air, a particular amount of time for the indoor interaction, and that all individuals are homogeneous and behave equally. Here, we revisit the Wells-Riley model, providing a mathematical formalism for its stochastic version, where the number of infected individuals follows a Binomial distribution. Then, we extend the Wells-Riley methodology to consider transient behaviours, randomness, and population heterogeneity. In particular, we provide analytical solutions for the number of infections and the per capita probability of infection when: (i) susceptible individuals remain in the room after the infector leaves, (ii) the duration of the indoor interaction is random/unknown, and (iii) infectors have heterogeneous quanta production rates (or the quanta production rate of the infector is random/unknown). We illustrate the applicability of our new formulations through two case studies: infection risk due to an infectious healthcare worker (HCW) visiting a patient, and exposure during lunch for uncertain meal times in different dining settings. Our results highlight that infection risk to a susceptible who remains in the space after the infector leaves can be nonnegligible, and highlight the importance of incorporating uncertainty in the duration of the indoor interaction and the infectivity of the infector when estimating risk.

Impact of COVID-19 Pandemic on Routine Childhood Immunization Programs in Indonesia: Taking Rural and Urban Area into Account

Background

To date, the primary global concern has revolved around addressing the COVID-19 pandemic. However, there is a growing awareness of the pandemic's secondary impacts on critical aspects of healthcare, such as childhood immunization programs.

Objective

This study aims to assess the impact of the COVID-19 pandemic on childhood immunization programs in Indonesia, with a specific focus on performance disparities between rural and urban areas. It considers factors like access, utilization, and program workload.

Methods

Data were collected from primary health cares (PHCs) in two regions in West Java Province, Indonesia, representing rural and urban areas. A descriptive analysis was conducted to compare vaccination coverage, drop-out rates, and the ratio of vaccinators per dose from 2019 to 2021 in 40 and 22 PHCs for rural and urban areas, respectively. A general linear model was employed to evaluate the differences in these parameters over the three consecutive years.

Results

The results indicate fluctuations in vaccine coverage over the three years, with the most significant impact observed in 2020, particularly in rural areas. Statistical analysis revealed a significant difference in routine immunization coverage, drop-out rates, and vaccinator ratios between rural and urban areas from 2019 to 2021 (p<0.05). In 2021, both rural and urban areas displayed significant differences in performance parameters for routine immunization and COVID-19 vaccination (p<0.05), except in terms of coverage for IPV and COVID-19 vaccination.

Conclusion

The study highlights a reduction in routine immunization coverage during the pandemic, a concerning issue that increases the risk of vaccine-preventable diseases, particularly in rural areas.

Advancements in Airborne Viral Nucleic Acid Detection with Wearable Devices

Wearable health sensors for an expanding range of physiological parameters have experienced rapid development in recent years and are poised to disrupt the way healthcare is tracked and administered. The monitoring of environmental contaminants with wearable technologies is an additional layer of personal and public healthcare and is also receiving increased focus. Wearable sensors that detect exposure to airborne viruses could alert wearers of viral exposure and prompt proactive testing and minimization of viral spread, benefitting their own health and decreasing community risk. With the high levels of asymptomatic spread of COVID-19 observed during the pandemic, such devices could dramatically enhance our pandemic response capabilities in the future. To facilitate advancements in this area, this review summarizes recent research on airborne viral detection using wearable sensing devices as well as technologies suitable for wearables. Since the low concentration of viral particles in the air poses significant challenges to detection, methods for airborne viral particle collection and viral sensing are discussed in detail. A special focus is placed on nucleic acid-based viral sensing mechanisms due to their enhanced ability to discriminate between viral subtypes. Important considerations for integrating airborne viral collection and sensing on a single wearable device are also discussed.

A critical review of research methodologies for COVID-19 transmission in indoor built environment

The Coronavirus Disease 2019 (COVID-19) has caused massive losses for the global economy. Scholars have used different methods to study the transmission mode and influencing factors of the virus to find effective methods to provide people with a healthy built environment. However, these studies arrived at different or even contradictory conclusions. This review presents the main research methodologies utilized in this field, summarizes the main investigation methods, and critically discusses their related conclusions. Data statistical analysis, sample collection, simulation models, and replication transmission scenarios are the main research methods. The summarized conclusion for prevention from all reviewed papers are: adequate ventilation and proper location of return air vents, proper use of personal protective equipment, as well as the reasonable and strict enforcement of policies are the main methods for reducing the transmission. Recommendations including standardized databases, causation clarification, rigorous experiment design, improved simulation accuracy and verification are provided.

Estimating the prevalence of COVID-19 cases through the analysis of SARS-CoV-2 RNA copies derived from wastewater samples from North Dakota

The SARS-CoV-2 virus was first detected in December 2019, which prompted many researchers to investigate how the virus spreads. SARS-CoV-2 is mainly transmitted through respiratory droplets. Symptoms of the SARS-CoV-2 virus appear after an incubation period. Moreover, the asymptomatic infected individuals unknowingly spread the virus. Detecting infected people requires daily tests and contact tracing, which are expensive. The early detection of infectious diseases, including COVID-19, can be achieved with wastewater-based epidemiology, which is timely and cost-effective. In this study, we collected wastewater samples from wastewater treatment plants in several cities in North Dakota and then extracted viral RNA copies. We used log-RNA copies in the model to predict the number of infected cases using Quantile Regression (QR) and K-Nearest Neighbor (KNN) Regression. The model's performance was evaluated by comparing the Mean Absolute Percentage Error (MAPE). The QR model performs well in cities where the population is >10000 . In addition, the model predictions were compared with the basic Susceptible-Infected-Recovered (SIR) model which is the golden standard model for infectious diseases.

Geoepidemiological perspective on COVID-19 pandemic review, an insight into the global impact

The COVID-19 pandemic showed major impacts, on societies worldwide, challenging healthcare systems, economies, and daily life of people. Geoepidemiology, an emerging field that combines geography and epidemiology, has played a vital role in understanding and combatting the spread of the virus. This interdisciplinary approach has provided insights into the spatial patterns, risk factors, and transmission dynamics of the COVID-19 pandemic at different scales, from local communities to global populations. Spatial patterns have revealed variations in incidence rates, with urban-rural divides and regional hotspots playing significant roles. Cross-border transmission has highlighted the importance of travel restrictions and coordinated public health responses. Risk factors such as age, underlying health conditions, socioeconomic factors, occupation, demographics, and behavior have influenced vulnerability and outcomes. Geoepidemiology has also provided insights into the transmissibility and spread of COVID-19, emphasizing the importance of asymptomatic and pre-symptomatic transmission, super-spreading events, and the impact of variants. Geoepidemiology should be vital in understanding and responding to evolving new viral challenges of this and future pandemics.

Mesenchymal Stem Cells in the Treatment of COVID-19

Since the emergence of the coronavirus disease 2019 (COVID-19) pandemic, many lives have been tragically lost to severe infections. The COVID-19 impact extends beyond the respiratory system, affecting various organs and functions. In severe cases, it can progress to acute respiratory distress syndrome (ARDS) and multi-organ failure, often fueled by an excessive immune response known as a cytokine storm. Mesenchymal stem cells (MSCs) have considerable potential because they can mitigate inflammation, modulate immune responses, and promote tissue regeneration. Accumulating evidence underscores the efficacy and safety of MSCs in treating severe COVID-19 and ARDS. Nonetheless, critical aspects, such as optimal routes of MSC administration, appropriate dosage, treatment intervals, management of extrapulmonary complications, and potential pediatric applications, warrant further exploration. These research avenues hold promise for enriching our understanding and refining the application of MSCs in confronting the multifaceted challenges posed by COVID-19.

Risk of Testing Positive for COVID-19 among Healthcare and Healthcare-Related Workers

Understanding the risk factors associated with COVID-19 infection among healthcare workers is crucial for infection prevention and control. The aim of this study was to examine the risk of testing positive for COVID-19 among a multicenter cohort of workers, taking into account their occupational roles (medical professionals, staff in operational and administrative roles, or laboratory personnel) in healthcare settings. The data analyzed in this study included 2163 individuals with suggestive COVID-19 symptoms who underwent laboratory testing. The incidence rate in the study sample was calculated to be 15.3 cases per 10,000 person-days. The results from the multiple regression model indicated that job roles were not significantly associated with the risk of testing positive. However, age and the duration of the pandemic were identified as significant risk factors, with increasing age and longer pandemic duration being associated with a higher risk of testing positive. Additionally, vaccination was found to reduce the risk of testing positive. These findings provide valuable insights into COVID-19 transmission among indoor healthcare workers, highlighting the influence of age, pandemic duration, and vaccination on infection risk. Further research is needed to develop evidence-based strategies aimed at protecting healthcare workers and preventing virus spread in healthcare settings.

Virus-laden droplet nuclei in vortical structures associated with recirculation zones in indoor environments: A possible airborne transmission of SARS-CoV-2

Droplet nuclei dispersion patterns in indoor environments are reviewed from a physics view to explore the possibility of airborne transmission of SARS-CoV-2. This review analyzes works on particle dispersion patterns and their concentration in vortical structures in different indoor environments. Numerical simulations and experiments reveal the formation of the buildings' recirculation zones and vortex flow regions by flow separation, airflow interaction around objects, internal dispersion of airflow, or thermal plume. These vortical structures showed high particle concentration because particles are trapped for long periods. Then a hypothesis is proposed to explain why some medical studies detect the presence of SARS-CoV-2 and others do not detect the virus. The hypothesis proposes that airborne transmission is possible if virus-laden droplet nuclei are trapped in vortical structures associated with recirculation zones. This hypothesis is reinforced by a numerical study in a restaurant that presented possible evidence of airborne transmission by a large recirculating air zone. Furthermore, a medical study in a hospital is discussed from a physical view for identifying the formation of recirculation zones and their relation with positive tests for viruses. The observations show air sampling site located in this vortical structure is positive for the SARS-CoV-2 RNA. Therefore, the formation of vortical structures associated with recirculation zones should be avoided to minimize the possibility of airborne transmission. This work tries to understand the complex phenomenon of airborne transmission as a way in the prevention of transmission of infectious diseases.

Between-occupation differences in work-related COVID-19 mitigation strategies over time: Analysis of the Virus Watch Cohort in England and Wales

OBJECTIVES

COVID-19 mitigations have had a profound impact on workplaces, however, multisectoral comparisons of how work-related mitigations were applied are limited. This study aimed to investigate (i) occupational differences in the usage of key work-related mitigations over time and (ii) workers' perceptions of these mitigations.

METHODS

Employed/self-employed Virus Watch study participants (N=6279) responded to a mitigation-related online survey covering the periods of December 2020-February 2022. Logistic regression was used to investigate occupation- and time-related differences in the usage of work-related mitigation methods. Participants' perceptions of mitigation methods were investigated descriptively using proportions.

RESULTS

Usage of work-related mitigation methods differed between occupations and over time, likely reflecting variation in job roles, workplace environments, legislation and guidance. Healthcare workers had the highest predicted probabilities for several mitigations, including reporting frequent hand hygiene [predicted probability across all survey periods 0.61 (95% CI 0.56-0.66)] and always wearing face coverings [predicted probability range 0.71 (95% CI 0.66-0.75) - 0.80 (95% CI 0.76-0.84) across survey periods]. There were significant cross-occupational trends towards reduced mitigations during periods of less stringent national restrictions. The majority of participants across occupations (55-88%) agreed that most mitigations were reasonable and worthwhile even after the relaxation of national restrictions; agreement was lower for physical distancing (39-44%).

CONCLUSIONS

While usage of work-related mitigations appeared to vary alongside stringency of national restrictions, agreement that most mitigations were reasonable and worthwhile remained substantial. Further investigation into the factors underlying between-occupational differences could assist pandemic planning and prevention of workplace COVID-19 transmission.

Transmission and infection risk of COVID-19 when people coughing in an elevator

People in cities use elevators daily. With the COVID-19 pandemic, there are more worries about elevator safety, since elevators are often small and crowded. This study used a proven CFD model to see how the virus could spread in elevators. We simulated five people taking in an elevator for 2 min and analyzed the effect of different factors on the amount of virus that could be inhaled, such as the infected person's location, the standing positions of the persons, and the air flow rate. We found that the position of the infected person and the direction they stood greatly impacted virus transmission in the elevator. The use of mechanical ventilation with a flow rate of 30 ACH (air changes per hour) was effective in reducing the risk of infection. In situations where the air flow rate was 3 ACH, we found that the highest number of inhaled virus copies could range from 237 to 1186. However, with a flow rate of 30 ACH, the highest number was reduced to 153 to 509. The study also showed that wearing surgical masks decreased the highest number of inhaled virus copies to 74 to 155.

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.

A Comparison of the Effect of Facemasks on Perceived Breathability and Air Quality during Daily Activities and Indoor Exercises

Transmission of COVID-19 occurs predominantly through respired droplets and aerosols containing the SARS-CoV-2 virus. As a solution, face masks have been used to protect against infection. Wearing face masks during indoor exercises is essential to prevent the spread of virus-containing respiratory droplets and aerosols. However, previous studies have not investigated all elements, including the users' perceived breathability (PB) and perceived air quality (PAQ) when wearing a face mask during indoor exercises. The current study aimed to assess users' perceived comfort (PC) of face masks based on assessment criteria of PB and PAQ during moderate to vigorous exercises, and compare them with those during normal daily activities. Data on PC, PB, and PAQ were collected from an online questionnaire survey from 104 participants doing regular moderate to vigorous exercises. Within-subjects comparison with self-controlled case series design was performed to compare PC, PB, and PAQ between wearing face masks during exercises and daily activities. Results showed that the degree of dissatisfaction with PC, PB, and PAQ while wearing face masks and performing indoor exercises is higher than when performing daily activities (p < 0.05). The significance of the study implies that masks comfortable for daily activities may not remain the same during moderate to vigorous exercises, especially during indoor exercises.

Identifying spatiotemporal information of the point pollutant source indoors based on the adjoint-regularization method

Fast and accurate identification of the pollutant source location and release rate is important for improving indoor air quality. From the perspective of public health, identification of the airborne pathogen source in public buildings is particularly important for ensuring people's safety and health. The existing adjoint probability method has difficulty in distinguishing the temporal source, and the optimization algorithm can only analyze a few potential sources in space. This study proposed an algorithm combining the adjoint-pulse and regularization methods to identify the spatiotemporal information of the point pollutant source in an entire room space. We first obtained a series of source-receptor response matrices using the adjoint-pulse method in the room based on the validated CFD model, and then used the regularization method and composite Bayesian inference to identify the release rate and location of the dynamic pollutant source. The results showed that the MAPEs (mean absolute percentage errors) of estimated source intensities were almost less than 15%, and the source localization success rates were above 25/30 in this study. This method has the potential to be used to identify the airborne pathogen source in public buildings combined with sensors for disease-specific biomarkers.

An excimer lamp to provide far-ultraviolet C irradiation for dining-table disinfection

Dining tables may present a risk to diners by transmitting bacteria and/or viruses. Currently, there is a lack of an environmental-friendly and convenient means to protect diners when they are sitting together. This investigation constructed far-UVC excimer lamps to disinfect dining-table surfaces. The lamps were mounted at different heights and orientations, and the irradiance on table surfaces was measured. The irradiation doses to obtain different inactivation efficiencies for Escherichia coli (E. coli) were provided. In addition, numerical modeling was conducted for irradiance and the resulting inactivation efficiency. The surface-to-surface (S2S) model was validated with the measured irradiance. The germicidal performance of far-UVC irradiation, the far-UVC doses to which diners were exposed, and the risk of exposure to the generated ozone were evaluated. The results revealed that an irradiation dose of 12.8 mJ/cm2 can disinfect 99.9% of E. coli on surfaces. By varying the lamp irradiance output, the number and positions of the lamps, the far-UVC irradiation can achieve a 3-log reduction for a dining duration of 5 min. Besides, the far-UVC lamp has a low damage risk to diners when achieving an effective inactivation rate. Moreover, there is virtually no ozone exposure risk in a mechanically ventilated dining hall.

Unanswered questions on the airborne transmission of COVID-19

Policies and measures to control pandemics are often failing. While biological factors controlling transmission are usually well explored, little is known about the environmental drivers of transmission and infection. For instance, respiratory droplets and aerosol particles are crucial vectors for the airborne transmission of the severe acute respiratory syndrome coronavirus 2, the causation agent of the coronavirus 2019 pandemic (COVID-19). Once expectorated, respiratory droplets interact with atmospheric particulates that influence the viability and transmission of the novel coronavirus, yet there is little knowledge on this process or its consequences on virus transmission and infection. Here we review the effects of atmospheric particulate properties, vortex zones, and air pollution on virus survivability and transmission. We found that particle size, chemical constituents, electrostatic charges, and the moisture content of airborne particles can have notable effects on virus transmission, with higher survival generally associated with larger particles, yet some viruses are better preserved on small particles. Some chemical constituents and surface-adsorbed chemical species may damage peptide bonds in viral proteins and impair virus stability. Electrostatic charges and water content of atmospheric particulates may affect the adherence of virion particles and possibly their viability. In addition, vortex zones and human thermal plumes are major environmental factors altering the aerodynamics of buoyant particles in air, which can strongly influence the transport of airborne particles and the transmission of associated viruses. Insights into these factors may provide explanations for the widely observed positive correlations between COVID-19 infection and mortality with air pollution, of which particulate matter is a common constituent that may have a central role in the airborne transmission of the novel coronavirus.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10311-022-01557-z.

Response to the COVID-19 Pandemic in Classrooms at the University of the Basque Country through a User-Informed Natural Ventilation Demonstrator

The COVID-19 pandemic has generated a renewed interest in indoor air quality to limit viral spread. In the case of educational spaces, due to the high concentration of people and the fact that most of the existing buildings do not have any mechanical ventilation system, the different administrations have established natural ventilation protocols to guarantee an air quality that reduces risk of contagion by the SARS-CoV-2 virus after the return to the classrooms. Many of the initial protocols established a ventilation pattern that opted for continuous or intermittent ventilation to varying degrees of intensity. This study, carried out on a university campus in Spain, analyses the performance of natural ventilation activated through the information provided by monitoring and visualisation of real-time data. In order to carry out this analysis, a experiment was set up where a preliminary study of ventilation without providing information to the users was carried out, which was then compared with the result of providing live feedback to the occupants of two classrooms and an administration office in different periods of 2020, 2021 and 2022. In the administration office, a CO2-concentration-based method was applied retrospectively to assess the risk of airborne infection. This experience has served as a basis to establish a route for user-informed improvement of air quality in educational spaces in general through low-cost systems that allow a rational use of natural ventilation while helping maintain an adequate compromise between IAQ, comfort and energy consumption, without having to resort to mechanical ventilation systems.

Application of data-driven RANS model in simulating indoor airflow

The indoor environment has a significant impact on our wellbeing. Accurate prediction of the indoor air distribution can help to create a good indoor environment. Reynolds-averaged Navier-Stokes (RANS) models are commonly used for indoor airflow prediction. However, the Boussinesq hypothesis used in the RANS model fails to account for indoor anisotropic flows. To solve this problem, this study developed a data-driven RANS model by using a nonlinear model from the literature. An artificial neural network (ANN) was used to determine the coefficients of high-order terms. Three typical indoor airflows were selected as the training set to develop the model. Four other cases were used as testing sets to verify the generalizability of the model. The results show that the data-driven model can better predict the distributions of air velocity, temperature, and turbulent kinetic energy for the indoor anisotropic flows than the original RANS model. This is because the nonlinear terms are accurately simulated by the ANN. This investigation concluded that the data-driven model can correctly predict indoor anisotropic flows and has reasonably good generalizability.

An evaluation of the risk of airborne transmission of COVID-19 on an inter-city train carriage

Experiments were conducted in an UK inter-city train carriage with the aim of evaluating the risk of infection to the SARS-CoV-2 virus via airborne transmission. The experiments included in-service CO₂ measurements and the measurement of salt aerosol concentrations released within the carriage. Computational fluid dynamics simulations of the carriage airflow were also used to visualise the airflow patterns, and the efficacy of the HVAC filter material was tested in a laboratory. Assuming an infectious person is present, the risk of infection for a 1-h train journey was estimated to be 6 times lower than for a full day in a well-ventilated office, or 10-12 times lower than a full day in a poorly ventilated office. While the absolute risk for a typical journey is likely low, in the case where a particularly infectious individual is on-board, there is the potential for a number of secondary infections to occur during a 1-h journey. Every effort should therefore be made to minimize the risk of airborne infection within these carriages. Recommendations are also given for the use of CO₂ sensors for the evaluation of the risk of airborne transmission on train carriages.

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.