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Database of SARS-CoV-2 and coronaviruses kinetics relevant for assessing persistence in food processing plants
SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2), a virus causing severe acute respiratory disease in humans, emerged in late 2019. This respiratory virus can spread via aerosols, fomites, contaminated hands or surfaces as for other coronaviruses. Studying their persistence under differe...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9606249/ https://www.ncbi.nlm.nih.gov/pubmed/36289246 http://dx.doi.org/10.1038/s41597-022-01763-y |
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author | Luong, Ngoc-Du Martin Guillier, Laurent Martin-Latil, Sandra Batejat, Christophe Leclercq, India Druesne, Christine Sanaa, Moez Chaix, Estelle |
author_facet | Luong, Ngoc-Du Martin Guillier, Laurent Martin-Latil, Sandra Batejat, Christophe Leclercq, India Druesne, Christine Sanaa, Moez Chaix, Estelle |
author_sort | Luong, Ngoc-Du Martin |
collection | PubMed |
description | SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2), a virus causing severe acute respiratory disease in humans, emerged in late 2019. This respiratory virus can spread via aerosols, fomites, contaminated hands or surfaces as for other coronaviruses. Studying their persistence under different environmental conditions represents a key step for better understanding the virus transmission. This work aimed to present a reproducible procedure for collecting data of stability and inactivation kinetics from the scientific literature. The aim was to identify data useful for characterizing the persistence of viruses in the food production plants. As a result, a large dataset related to persistence on matrices or in liquid media under different environmental conditions is presented. This procedure, combining bibliographic survey, data digitalization techniques and predictive microbiological modelling, identified 65 research articles providing 455 coronaviruses kinetics. A ranking step as well as a technical validation with a Gage Repeatability & Reproducibility process were performed to check the quality of the kinetics. All data were deposited in public repositories for future uses by other researchers. |
format | Online Article Text |
id | pubmed-9606249 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96062492022-10-28 Database of SARS-CoV-2 and coronaviruses kinetics relevant for assessing persistence in food processing plants Luong, Ngoc-Du Martin Guillier, Laurent Martin-Latil, Sandra Batejat, Christophe Leclercq, India Druesne, Christine Sanaa, Moez Chaix, Estelle Sci Data Data Descriptor SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2), a virus causing severe acute respiratory disease in humans, emerged in late 2019. This respiratory virus can spread via aerosols, fomites, contaminated hands or surfaces as for other coronaviruses. Studying their persistence under different environmental conditions represents a key step for better understanding the virus transmission. This work aimed to present a reproducible procedure for collecting data of stability and inactivation kinetics from the scientific literature. The aim was to identify data useful for characterizing the persistence of viruses in the food production plants. As a result, a large dataset related to persistence on matrices or in liquid media under different environmental conditions is presented. This procedure, combining bibliographic survey, data digitalization techniques and predictive microbiological modelling, identified 65 research articles providing 455 coronaviruses kinetics. A ranking step as well as a technical validation with a Gage Repeatability & Reproducibility process were performed to check the quality of the kinetics. All data were deposited in public repositories for future uses by other researchers. Nature Publishing Group UK 2022-10-26 /pmc/articles/PMC9606249/ /pubmed/36289246 http://dx.doi.org/10.1038/s41597-022-01763-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Luong, Ngoc-Du Martin Guillier, Laurent Martin-Latil, Sandra Batejat, Christophe Leclercq, India Druesne, Christine Sanaa, Moez Chaix, Estelle Database of SARS-CoV-2 and coronaviruses kinetics relevant for assessing persistence in food processing plants |
title | Database of SARS-CoV-2 and coronaviruses kinetics relevant for assessing persistence in food processing plants |
title_full | Database of SARS-CoV-2 and coronaviruses kinetics relevant for assessing persistence in food processing plants |
title_fullStr | Database of SARS-CoV-2 and coronaviruses kinetics relevant for assessing persistence in food processing plants |
title_full_unstemmed | Database of SARS-CoV-2 and coronaviruses kinetics relevant for assessing persistence in food processing plants |
title_short | Database of SARS-CoV-2 and coronaviruses kinetics relevant for assessing persistence in food processing plants |
title_sort | database of sars-cov-2 and coronaviruses kinetics relevant for assessing persistence in food processing plants |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9606249/ https://www.ncbi.nlm.nih.gov/pubmed/36289246 http://dx.doi.org/10.1038/s41597-022-01763-y |
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