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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 prevent...

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Autores principales: Yang, Ying-Fei, Lin, Yi-Jun, You, Shu-Han, Lu, Tien-Hsuan, Chen, Chi-Yun, Wang, Wei-Min, Liao, Chung-Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9772602/
https://www.ncbi.nlm.nih.gov/pubmed/36547825
http://dx.doi.org/10.1007/s11356-022-24815-7
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author Yang, Ying-Fei
Lin, Yi-Jun
You, Shu-Han
Lu, Tien-Hsuan
Chen, Chi-Yun
Wang, Wei-Min
Liao, Chung-Min
author_facet Yang, Ying-Fei
Lin, Yi-Jun
You, Shu-Han
Lu, Tien-Hsuan
Chen, Chi-Yun
Wang, Wei-Min
Liao, Chung-Min
author_sort Yang, Ying-Fei
collection PubMed
description 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 (R(0)) − 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-022-24815-7.
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spelling pubmed-97726022022-12-22 Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects Yang, Ying-Fei Lin, Yi-Jun You, Shu-Han Lu, Tien-Hsuan Chen, Chi-Yun Wang, Wei-Min Liao, Chung-Min Environ Sci Pollut Res Int Research Article 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 (R(0)) − 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-022-24815-7. Springer Berlin Heidelberg 2022-12-22 2023 /pmc/articles/PMC9772602/ /pubmed/36547825 http://dx.doi.org/10.1007/s11356-022-24815-7 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Research Article
Yang, Ying-Fei
Lin, Yi-Jun
You, Shu-Han
Lu, Tien-Hsuan
Chen, Chi-Yun
Wang, Wei-Min
Liao, Chung-Min
Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects
title Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects
title_full Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects
title_fullStr Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects
title_full_unstemmed Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects
title_short Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects
title_sort control measure implications of covid-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9772602/
https://www.ncbi.nlm.nih.gov/pubmed/36547825
http://dx.doi.org/10.1007/s11356-022-24815-7
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