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Kulmala I, Taipale A, Sanmark E, Lastovets N, Sormunen P, Nuorti P, Saari S, Luoto A, Säämänen A. Estimated relative potential for airborne SARS-CoV-2 transmission in a day care centre. Heliyon 2024; 10:e30724. [PMID: 38756615 PMCID: PMC11096945 DOI: 10.1016/j.heliyon.2024.e30724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 05/01/2024] [Accepted: 05/02/2024] [Indexed: 05/18/2024] Open
Abstract
We estimated the hourly probability of airborne severe acute respiratory coronavirus 2 (SARS-CoV-2) transmission and further the estimated number of persons at transmission risk in a day care centre by calculating the inhaled dose for airborne pathogens based on their concentration, exposure time and activity. Information about the occupancy and activity of the rooms was collected from day care centre personnel and building characteristics were obtained from the design values. The generation rate of pathogens was calculated as a product of viral load of the respiratory fluids and the emission of the exhaled airborne particles, considering the prevalence of the disease and the activity of the individuals. A well-mixed model was used in the estimation of the concentration of pathogens in the air. The Wells-Riley model was used for infection probability. The approach presented in this study was utilised in the identification of hot spots and critical events in the day care centre. Large variation in the infection probabilities and estimated number of persons at transmission risk was observed when modelling a normal day at the centre. The estimated hourly infection probabilities between the worst hour in the worst room and the best hour in the best room varied in the ratio of 100:1. Similarly, the number of persons at transmission risk between the worst and best cases varied in the ratio 1000:1. Although there are uncertainties in the input values affecting the absolute risk estimates the model proved to be useful in ranking and identifying the hot spots and events in the building and implementing effective control measures.
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Affiliation(s)
- Ilpo Kulmala
- VTT Smart Energy and Built Environment, Visiokatu 4, PO Box 1300, FI-33101, Tampere, Finland
| | - Aimo Taipale
- VTT Smart Energy and Built Environment, Visiokatu 4, PO Box 1300, FI-33101, Tampere, Finland
| | - Enni Sanmark
- Helsinki University Hospital, Department of Otorhinolaryngology and Phoniatrics – Head and Neck Surgery, Helsinki, Finland
- University of Helsinki, Helsinki, Finland
| | - Natalia Lastovets
- Tampere University, Faculty of Built Environment, Civil Engineering Unit, Korkeakoulunkatu 5D, FI-33720, Tampere, Finland
| | - Piia Sormunen
- Tampere University, Faculty of Built Environment, Civil Engineering Unit, Korkeakoulunkatu 5D, FI-33720, Tampere, Finland
| | - Pekka Nuorti
- Tampere University, Faculty of Social Sciences, Health Sciences Unit, Arvo Ylpön Katu 34, 33520, Tampere, Finland
| | - Sampo Saari
- Tampere University of Applied Sciences, Kuntokatu 3, 33520, Tampere, Finland
| | - Anni Luoto
- Granlund Oy, Malminkaari 21, 00700, Helsinki, Finland
| | - Arto Säämänen
- VTT Smart Energy and Built Environment, Visiokatu 4, PO Box 1300, FI-33101, Tampere, Finland
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Aganovic A, Kadric E. Does the exponential Wells-Riley model provide a good fit for human coronavirus and rhinovirus? A comparison of four dose-response models based on human challenge data. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2024; 44:631-640. [PMID: 37317640 DOI: 10.1111/risa.14178] [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: 01/31/2023] [Revised: 05/29/2023] [Accepted: 06/01/2023] [Indexed: 06/16/2023]
Abstract
The risk assessments during the COVID-19 pandemic were primarily based on dose-response models derived from the pooled datasets for infection of animals susceptible to SARS-CoV. Despite similarities, differences in susceptibility between animals and humans exist for respiratory viruses. The two most commonly used dose-response models for calculating the infection risk of respiratory viruses are the exponential and the Stirling approximated β-Poisson (BP) models. The modified version of the one-parameter exponential model or the Wells-Riley model was almost solely used for infection risk assessments during the pandemic. Still, the two-parameter (α and β) Stirling approximated BP model is often recommended compared to the exponential dose-response model due to its flexibility. However, the Stirling approximation restricts this model to the general rules of β ≫ 1 and α ≪ β, and these conditions are very often violated. To refrain from these requirements, we tested a novel BP model by using the Laplace approximation of the Kummer hypergeometric function instead of the conservative Stirling approximation. The datasets of human respiratory airborne viruses available in the literature for human coronavirus (HCoV-229E) and human rhinovirus (HRV-16 and HRV-39) are used to compare the four dose-response models. Based on goodness-of-fit criteria, the exponential model was the best fitting model for the HCoV-229E (k = 0.054) and for HRV-39 datasets (k = 1.0), whereas the Laplace approximated BP model followed by the exact and Stirling approximated BP models are preferred for both the HRV-16 (α = 0.152 and β = 0.021 for Laplace BP) and the HRV-16 and HRV-39 pooled datasets (α = 0.2247 and β = 0.0215 for Laplace BP).
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Affiliation(s)
- Amar Aganovic
- Faculty of Engineering Science and Technology, The Arctic University of Tromsø, Tromso, Norway
| | - Edin Kadric
- Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina
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Chen K. Holistic understanding of ventilation rate in occupational health risk control. Ann N Y Acad Sci 2024; 1531:3-11. [PMID: 38050986 DOI: 10.1111/nyas.15087] [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: 12/07/2023]
Abstract
Throughout the history of occupational health risk control, ventilation has been implemented widely as a tried-and-true method to reduce exposure intensity to airborne contaminants. Proper determination of the ventilation rate merits careful consideration when addressing concerns directed toward occupational health and indoor air quality in commercial buildings, albeit this does not translate well among the current engineering and scientific community. This article aims to facilitate a better understanding and proper determination of ventilation rates as a countermeasure for occupational health risk control. To that end, guidance is provided to select the appropriate ventilation rate for nonpandemic versus pandemic scenarios in terms of pertinent regulatory/professional codes and mathematical modeling tools. Limitations and assumptions of the models are summarized to facilitate proper application. Furthermore, the emerging DNA-based aerosol tracing technology, which helps to verify ventilation efficacy, is discussed.
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Affiliation(s)
- Kang Chen
- PetroChina Shanghai Advanced Materials Research Institute, Shanghai, China
- Capitol Technology University, Laurel, Maryland, USA
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Liao Y, Guo S, Mao N, Li Y, Li J, Long E. Animal experiments on respiratory viruses and analogous studies of infection factors for interpersonal transmission. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:66209-66227. [PMID: 37097557 PMCID: PMC10125856 DOI: 10.1007/s11356-023-26738-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 03/27/2023] [Indexed: 05/15/2023]
Abstract
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.
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Affiliation(s)
- Yuxuan Liao
- MOE Key Laboratory of Deep Earth Science and Engineering, Room 112, College of Architecture and Environment, Administration Building, Sichuan University, No. 24, First Loop South First Section, Chengdu, 610065, China
| | - Shurui Guo
- MOE Key Laboratory of Deep Earth Science and Engineering, Room 112, College of Architecture and Environment, Administration Building, Sichuan University, No. 24, First Loop South First Section, Chengdu, 610065, China
| | - Ning Mao
- Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, China
| | - Ying Li
- MOE Key Laboratory of Deep Earth Science and Engineering, Room 112, College of Architecture and Environment, Administration Building, Sichuan University, No. 24, First Loop South First Section, Chengdu, 610065, China
| | - Jin Li
- MOE Key Laboratory of Deep Earth Science and Engineering, Room 112, College of Architecture and Environment, Administration Building, Sichuan University, No. 24, First Loop South First Section, Chengdu, 610065, China
| | - Enshen Long
- MOE Key Laboratory of Deep Earth Science and Engineering, Room 112, College of Architecture and Environment, Administration Building, Sichuan University, No. 24, First Loop South First Section, Chengdu, 610065, China.
- Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, China.
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A review on indoor airborne transmission of COVID-19– modelling and mitigation approaches. JOURNAL OF BUILDING ENGINEERING 2023; 64:105599. [PMCID: PMC9699823 DOI: 10.1016/j.jobe.2022.105599] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 11/11/2022] [Accepted: 11/21/2022] [Indexed: 06/09/2023]
Abstract
In the past few years, significant efforts have been made to investigate the transmission of COVID-19. This paper provides a review of the COVID-19 airborne transmission modeling and mitigation strategies. The simulation models here are classified into airborne transmission infectious risk models and numerical approaches for spatiotemporal airborne transmissions. Mathematical descriptions and assumptions on which these models have been based are discussed. Input data used in previous simulation studies to assess the dispersion of COVID-19 are extracted and reported. Moreover, measurements performed to study the COVID-19 airborne transmission within indoor environments are introduced to support validations for anticipated future modeling studies. Transmission mitigation strategies recommended in recent studies have been classified to include modifying occupancy and ventilation operations, using filters and air purifiers, installing ultraviolet (UV) air disinfection systems, and personal protection compliance, such as wearing masks and social distancing. The application of mitigation strategies to various building types, such as educational, office, public, residential, and hospital, is reviewed. Recommendations for future works are also discussed based on the current apparent knowledge gaps covering both modeling and mitigation approaches. Our findings show that different transmission mitigation measures were recommended for various indoor environments; however, there is no conclusive work reporting their combined effects on the level of mitigation that may be achieved. Moreover, further studies should be conducted to understand better the balance between approaches to mitigating the viral transmissions in buildings and building energy consumption.
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Aganovic A, Cao G, Kurnitski J, Wargocki P. New dose-response model and SARS-CoV-2 quanta emission rates for calculating the long-range airborne infection risk. BUILDING AND ENVIRONMENT 2023; 228:109924. [PMID: 36531865 PMCID: PMC9747236 DOI: 10.1016/j.buildenv.2022.109924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/12/2022] [Accepted: 12/13/2022] [Indexed: 06/17/2023]
Abstract
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.
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Affiliation(s)
- Amar Aganovic
- Department of Automation and Process Engineering, UiT The Arctic University of Norway, Tromsø, Norway
| | - Guangyu Cao
- Department of Energy and Process Engineering, Norwegian University of Science and Technology - NTNU, Trondheim, Norway
| | - Jarek Kurnitski
- REHVA Technology and Research Committee, Tallinn University of Technology, Tallinn, Estonia
| | - Pawel Wargocki
- Department of Civil Engineering, Technical University of Denmark, Copenhagen, Denmark
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