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Application of layers of protection analysis to prevent coronavirus infection
Layers of protection analysis (LOPA) methodology is applied to an encounter with the SARS‐COV‐2 infection as an initiating event, and subsequently, independent protection layers (IPLs) (namely health safeguarding protocols), such as social distancing, ventilation, hand hygiene, face masks, and vacci...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9111029/ http://dx.doi.org/10.1002/prs.12362 |
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author | Mokhber, Ali Aggarwal, Shivani García‐Triñanes, Pablo |
author_facet | Mokhber, Ali Aggarwal, Shivani García‐Triñanes, Pablo |
author_sort | Mokhber, Ali |
collection | PubMed |
description | Layers of protection analysis (LOPA) methodology is applied to an encounter with the SARS‐COV‐2 infection as an initiating event, and subsequently, independent protection layers (IPLs) (namely health safeguarding protocols), such as social distancing, ventilation, hand hygiene, face masks, and vaccinations. LOPA is applied considering numerical quantification of the COVID fatality index in order to manage the transmission risk to a tolerable level, namely the fatality risk due to seasonal flu. This measurement tool quantifies the ratio of the annual death rate due to the SARS‐COV‐2 infection to the annual death rate of the common flu, and it is applied to a chemical plant. The lower this quantified value is, the more the COVID‐19 infection death rate approaches that of the common flu. Thus, any improvement in safeguarding protocols should reduce this index. The input data is based on public domain COVID‐19 infection statistical data and websites accessible in the United Kingdom. The COVID‐19 transmission rate is statistically analyzed with random number sampling to simulate the random pattern of the virus' person‐to‐person infection in the community. The success of the COVID‐19 protection protocols is probabilistic and depends on the public's compliance, which is modeled by observational surveys. |
format | Online Article Text |
id | pubmed-9111029 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91110292022-05-17 Application of layers of protection analysis to prevent coronavirus infection Mokhber, Ali Aggarwal, Shivani García‐Triñanes, Pablo Process Safety Progress Hazard Identification and Risk Analysis Layers of protection analysis (LOPA) methodology is applied to an encounter with the SARS‐COV‐2 infection as an initiating event, and subsequently, independent protection layers (IPLs) (namely health safeguarding protocols), such as social distancing, ventilation, hand hygiene, face masks, and vaccinations. LOPA is applied considering numerical quantification of the COVID fatality index in order to manage the transmission risk to a tolerable level, namely the fatality risk due to seasonal flu. This measurement tool quantifies the ratio of the annual death rate due to the SARS‐COV‐2 infection to the annual death rate of the common flu, and it is applied to a chemical plant. The lower this quantified value is, the more the COVID‐19 infection death rate approaches that of the common flu. Thus, any improvement in safeguarding protocols should reduce this index. The input data is based on public domain COVID‐19 infection statistical data and websites accessible in the United Kingdom. The COVID‐19 transmission rate is statistically analyzed with random number sampling to simulate the random pattern of the virus' person‐to‐person infection in the community. The success of the COVID‐19 protection protocols is probabilistic and depends on the public's compliance, which is modeled by observational surveys. John Wiley & Sons, Inc. 2022-03-31 2022-09 /pmc/articles/PMC9111029/ http://dx.doi.org/10.1002/prs.12362 Text en © 2022 The Authors. Process Safety Progress published by Wiley Periodicals LLC on behalf of American Institute of Chemical Engineers. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Hazard Identification and Risk Analysis Mokhber, Ali Aggarwal, Shivani García‐Triñanes, Pablo Application of layers of protection analysis to prevent coronavirus infection |
title | Application of layers of protection analysis to prevent coronavirus infection |
title_full | Application of layers of protection analysis to prevent coronavirus infection |
title_fullStr | Application of layers of protection analysis to prevent coronavirus infection |
title_full_unstemmed | Application of layers of protection analysis to prevent coronavirus infection |
title_short | Application of layers of protection analysis to prevent coronavirus infection |
title_sort | application of layers of protection analysis to prevent coronavirus infection |
topic | Hazard Identification and Risk Analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9111029/ http://dx.doi.org/10.1002/prs.12362 |
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