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Luo Q, Liu W, Liao J, Gu Z, Fan X, Luo Z, Zhang X, Hang J, Ou C. COVID-19 transmission and control in land public transport: A literature review. FUNDAMENTAL RESEARCH 2024; 4:417-429. [PMID: 38933205 PMCID: PMC11197583 DOI: 10.1016/j.fmre.2023.10.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 10/18/2023] [Accepted: 10/20/2023] [Indexed: 06/28/2024] Open
Abstract
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.
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Affiliation(s)
- Qiqi Luo
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
- Key Laboratory of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
- China Meteorological Administration Xiong'an Atmospheric Boundary Layer Key Laboratory, Xiong'an 070001, China
- Key Laboratory of Tropical Atmosphere-Ocean System (Sun Yat-sen University), Ministry of Education, Zhuhai 519000, China
| | - Wenbing Liu
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
| | - Jiayuan Liao
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
| | - Zhongli Gu
- Guangdong Fans-tech Agro Co., Ltd, Yunfu 527300, China
| | - Xiaodan Fan
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
| | - Zhiwen Luo
- Welsh School of Architecture, Cardiff University, Cardiff CF10 3XQ, United Kingdom
| | - Xuelin Zhang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
| | - Jian Hang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
- Key Laboratory of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
- China Meteorological Administration Xiong'an Atmospheric Boundary Layer Key Laboratory, Xiong'an 070001, China
- Key Laboratory of Tropical Atmosphere-Ocean System (Sun Yat-sen University), Ministry of Education, Zhuhai 519000, China
| | - Cuiyun Ou
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
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Pan Y, Huang W, Dai HK, Bian Y, Ho KF, Chen C. Evaluation of intervention measures in reducing the driver's exposure to respiratory particles in a taxi with infected passengers. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 902:166099. [PMID: 37558075 DOI: 10.1016/j.scitotenv.2023.166099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 08/02/2023] [Accepted: 08/05/2023] [Indexed: 08/11/2023]
Abstract
In the fifth wave of the COVID-19 epidemic in Hong Kong in early 2022, the large number of infected persons caused a shortage of ambulances and transportation vehicles operated by the government. To solve the problem, taxi drivers were recruited to transport infected persons to hospitals in their taxis. However, many of the drivers were infected after they began to participate in the plan. To tackle this issue, the present study numerically evaluated the effectiveness of several intervention measures in reducing the infection risk for taxi drivers. First, experiments were conducted inside a car to validate the large-eddy simulation (LES)-Lagrangian model for simulation of particle transport in a car. The validated model was then applied to calculate the particle dispersion and deposition in a Hong Kong taxi with intervention measures that included opening windows, installing partitions, and using a far-UVC lamp. The results show that opening the windows can significantly reduce the driver's total exposure by 97.4 %. Installing partitions and using a far-UVC lamp can further reduce the infection risk of driver by 55.9 % and 32.1 %, respectively. The results of this study can be used to support the implementation of effective intervention measures to protect taxi drivers from infection.
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Affiliation(s)
- Yue Pan
- Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong SAR, China
| | - Wenjie Huang
- Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong SAR, China
| | - Ho Kam Dai
- Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong SAR, China
| | - Ye Bian
- School of Energy and Environment, Southeast University, Nanjing 210096, China
| | - Kin-Fai Ho
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong SAR, China.
| | - Chun Chen
- Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong SAR, China; Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong SAR, China.
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Vita G, Woolf D, Avery-Hickmott T, Rowsell R. A CFD-based framework to assess airborne infection risk in buildings. BUILDING AND ENVIRONMENT 2023; 233:110099. [PMID: 36815961 PMCID: PMC9925846 DOI: 10.1016/j.buildenv.2023.110099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 01/31/2023] [Accepted: 02/12/2023] [Indexed: 06/18/2023]
Abstract
The COVID-19 pandemic has prompted huge efforts to further the scientific knowledge of indoor ventilation and its relationship to airborne infection risk. Exhaled infectious aerosols are spread and inhaled as a result of room airflow characteristics. Many calculation methods and assertions on risk assume 'well-mixed' flow conditions. However, ventilation in buildings is complex and often not showing well-mixed conditions. Ventilation guidance is typically based on the provision of generic minimum ventilation flow rates for a given space, irrespective of the effectiveness in the delivery of the supply air. Furthermore, the airflow might be heavily affected by the season, the HVAC ventilation, or the opening of windows, which would potentially generate draughts and non-uniform conditions. As a result, fresh air concentration would be variable depending upon a susceptible receptor's position in a room and, therefore, associated airborne infection risk. A computational fluid dynamics (CFD) and dynamic thermal modelling (DTM) framework is proposed to assess the influence of internal airflow characteristics on airborne infection risk. A simple metric is proposed, the hourly airborne infection rate (HAI) which can easily help designers to stress-test the ventilation within a building under several conditions. A case study is presented, and the results clearly demonstrate the importance of understanding detailed indoor airflow characteristics and associated concentration patterns in order to provide detailed design guidance, e.g. occupancy, supply air diffusers and furniture layouts, to reduce airborne infection risk.
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Affiliation(s)
- Giulio Vita
- Wirth Research Ltd, Charlotte Avenue, Bicester, OX27 8BL, United Kingdom
- University of Birmingham School of Engineering Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Darren Woolf
- Wirth Research Ltd, Charlotte Avenue, Bicester, OX27 8BL, United Kingdom
| | | | - Rob Rowsell
- Wirth Research Ltd, Charlotte Avenue, Bicester, OX27 8BL, United Kingdom
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Respiratory aerosol particle emission and simulated infection risk is greater during indoor endurance than resistance exercise. Proc Natl Acad Sci U S A 2023; 120:e2220882120. [PMID: 36802418 PMCID: PMC9992860 DOI: 10.1073/pnas.2220882120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023] Open
Abstract
Pathogens such as severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), influenza, and rhinoviruses are transmitted by airborne aerosol respiratory particles that are exhaled by infectious subjects. We have previously reported that the emission of aerosol particles increases on average 132-fold from rest to maximal endurance exercise. The aims of this study are to first measure aerosol particle emission during an isokinetic resistance exercise at 80% of the maximal voluntary contraction until exhaustion, second to compare aerosol particle emission during a typical spinning class session versus a three-set resistance training session. Finally, we then used this data to calculate the risk of infection during endurance and resistance exercise sessions with different mitigation strategies. During a set of isokinetic resistance exercise, aerosol particle emission increased 10-fold from 5,400 ± 1,200 particles/min at rest to 59,000 ± 69,900 particles/min during a set of resistance exercise. We found that aerosol particle emission per minute is on average 4.9-times lower during a resistance training session than during a spinning class. Using this data, we determined that the simulated infection risk increase during an endurance exercise session was sixfold higher than during a resistance exercise session when assuming one infected participant in the class. Collectively, this data helps to select mitigation measures for indoor resistance and endurance exercise classes at times where the risk of aerosol-transmitted infectious disease with severe outcomes is high.
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Nishandar SR, He Y, Princevac M, Edwards RD. Fate of Exhaled Droplets From Breathing and Coughing in Supermarket Checkouts and Passenger Cars. ENVIRONMENTAL HEALTH INSIGHTS 2023; 17:11786302221148274. [PMID: 36644342 PMCID: PMC9834932 DOI: 10.1177/11786302221148274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 12/12/2022] [Indexed: 06/17/2023]
Abstract
The global pandemic of COVID-19 has highlighted the importance of understanding the role that exhaled droplets play in virus transmission in community settings. Computational Fluid Dynamics (CFD) enables systematic examination of roles the exhaled droplets play in the spread of SARS-CoV-2 in indoor environments. This analysis uses published exhaled droplet size distributions combined with terminal aerosol droplet size based on measured peak concentrations for SARS-CoV-2 RNA in aerosols to simulate exhaled droplet dispersion, evaporation, and deposition in a supermarket checkout area and rideshare car where close proximity with other individuals is common. Using air inlet velocity of 2 m/s in the passenger car and ASHRAE recommendations for ventilation and comfort in the supermarket, simulations demonstrate that exhaled droplets <20 μm that contain the majority of viral RNA evaporated leaving residual droplet nuclei that remain aerosolized in the air. Subsequently ~ 70% of these droplet nuclei deposited in the supermarket and the car with the reminder vented from the space. The maximum surface deposition of droplet nuclei/m2 for speaking and coughing were 2 and 819, 18 and 1387 for supermarket and car respectively. Approximately 15% of the total exhaled droplets (aerodynamic diameters 20-700 µm) were deposited on surfaces in close proximity to the individual. Due to the non-linear distribution of viral RNA across droplet sizes, however, these larger exhaled droplets that deposit on surfaces have low viral content. Maximum surface deposition of viral RNA was 70 and 1.7 × 103 virions/m2 for speaking and 2.3 × 104 and 9.3 × 104 virions/m2 for coughing in the supermarket and car respectively while the initial airborne concentration of viral RNA was 7 × 106 copies per ml. Integrating the droplet size distributions with viral load distributions, this study helps explain the apparent importance of inhalation exposures compared to surface contact observed in the pandemic.
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Affiliation(s)
- Sanika Ravindra Nishandar
- Department of Mechanical Engineering,
Bourns College of Engineering, University of California, Riverside, CA, USA
| | - Yucheng He
- Department of Mechanical Engineering,
Bourns College of Engineering, University of California, Riverside, CA, USA
| | - Marko Princevac
- Department of Mechanical Engineering,
Bourns College of Engineering, University of California, Riverside, CA, USA
| | - Rufus D Edwards
- Department of Epidemiology, Program in
Public Health, University of California Irvine, CA, USA
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Buonanno G, Ricolfi L, Morawska L, Stabile L. Increasing ventilation reduces SARS-CoV-2 airborne transmission in schools: A retrospective cohort study in Italy's Marche region. Front Public Health 2022; 10:1087087. [PMID: 36568748 PMCID: PMC9787545 DOI: 10.3389/fpubh.2022.1087087] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 11/25/2022] [Indexed: 12/13/2022] Open
Abstract
Introduction While increasing the ventilation rate is an important measure to remove inhalable virus-laden respiratory particles and lower the risk of infection, direct validation in schools with population-based studies is far from definitive. Methods We investigated the strength of association between ventilation and SARS-CoV-2 transmission reported among the students of Italy's Marche region in more than 10,000 classrooms, of which 316 were equipped with mechanical ventilation. We used ordinary and logistic regression models to explore the relative risk associated with the exposure of students in classrooms. Results and discussion For classrooms equipped with mechanical ventilation systems, the relative risk of infection of students decreased at least by 74% compared with a classroom with only natural ventilation, reaching values of at least 80% for ventilation rates >10 L s-1 student-1. From the regression analysis we obtained a relative risk reduction in the range 12%15% for each additional unit of ventilation rate per person. The results also allowed to validate a recently developed predictive theoretical approach able to estimate the SARS-CoV-2 risk of infection of susceptible individuals via the airborne transmission route. We need mechanical ventilation systems to protect students in classrooms from airborne transmission; the protection is greater if ventilation rates higher than the rate needed to ensure indoor air quality (>10 L s-1 student-1) are adopted. The excellent agreement between the results from the retrospective cohort study and the outcome of the predictive theoretical approach makes it possible to assess the risk of airborne transmission for any indoor environment.
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Affiliation(s)
- Giorgio Buonanno
- Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, Italy,International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Luca Ricolfi
- Department of Psychology, University of Turin, Turin, Italy,David Hume Foundation, Turin, Italy
| | - Lidia Morawska
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Luca Stabile
- Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, Italy,*Correspondence: Luca Stabile
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Chen B, Liu S, Liu J, Jiang N, Chen Q. Application of data-driven RANS model in simulating indoor airflow. INDOOR AIR 2022; 32. [PMID: 36305074 DOI: 10.1111/ina.13123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 09/05/2022] [Accepted: 09/17/2022] [Indexed: 06/16/2023]
Abstract
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.
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Affiliation(s)
- Bingqian Chen
- Tianjin Key Laboratory of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin, China
| | - Sumei Liu
- Tianjin Key Laboratory of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin, China
| | - Junjie Liu
- Tianjin Key Laboratory of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin, China
| | - Nan Jiang
- School of Mechanical Engineering, Tianjin University, Tianjin, China
| | - Qingyan Chen
- Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong, China
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