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SARS-ANI: a global open access dataset of reported SARS-CoV-2 events in animals

The zoonotic origin of SARS-CoV-2, the etiological agent of COVID-19, is not yet fully resolved. Although natural infections in animals are reported in a wide range of species, large knowledge and data gaps remain regarding SARS-CoV-2 in animal hosts. We used two major health databases to extract un...

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Autores principales: Nerpel, Afra, Yang, Liuhuaying, Sorger, Johannes, Käsbohrer, Annemarie, Walzer, Chris, Desvars-Larrive, Amélie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308035/
https://www.ncbi.nlm.nih.gov/pubmed/35871228
http://dx.doi.org/10.1038/s41597-022-01543-8
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author Nerpel, Afra
Yang, Liuhuaying
Sorger, Johannes
Käsbohrer, Annemarie
Walzer, Chris
Desvars-Larrive, Amélie
author_facet Nerpel, Afra
Yang, Liuhuaying
Sorger, Johannes
Käsbohrer, Annemarie
Walzer, Chris
Desvars-Larrive, Amélie
author_sort Nerpel, Afra
collection PubMed
description The zoonotic origin of SARS-CoV-2, the etiological agent of COVID-19, is not yet fully resolved. Although natural infections in animals are reported in a wide range of species, large knowledge and data gaps remain regarding SARS-CoV-2 in animal hosts. We used two major health databases to extract unstructured data and generated a global dataset of SARS-CoV-2 events in animals. The dataset presents harmonized host names, integrates relevant epidemiological and clinical data on each event, and is readily usable for analytical purposes. We also share the code for technical and visual validation of the data and created a user-friendly dashboard for data exploration. Data on SARS-CoV-2 occurrence in animals is critical to adapting monitoring strategies, preventing the formation of animal reservoirs, and tailoring future human and animal vaccination programs. The FAIRness and analytical flexibility of the data will support research efforts on SARS-CoV-2 at the human-animal-environment interface. We intend to update this dataset weekly for at least one year and, through collaborations, to develop it further and expand its use.
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spelling pubmed-93080352022-07-25 SARS-ANI: a global open access dataset of reported SARS-CoV-2 events in animals Nerpel, Afra Yang, Liuhuaying Sorger, Johannes Käsbohrer, Annemarie Walzer, Chris Desvars-Larrive, Amélie Sci Data Data Descriptor The zoonotic origin of SARS-CoV-2, the etiological agent of COVID-19, is not yet fully resolved. Although natural infections in animals are reported in a wide range of species, large knowledge and data gaps remain regarding SARS-CoV-2 in animal hosts. We used two major health databases to extract unstructured data and generated a global dataset of SARS-CoV-2 events in animals. The dataset presents harmonized host names, integrates relevant epidemiological and clinical data on each event, and is readily usable for analytical purposes. We also share the code for technical and visual validation of the data and created a user-friendly dashboard for data exploration. Data on SARS-CoV-2 occurrence in animals is critical to adapting monitoring strategies, preventing the formation of animal reservoirs, and tailoring future human and animal vaccination programs. The FAIRness and analytical flexibility of the data will support research efforts on SARS-CoV-2 at the human-animal-environment interface. We intend to update this dataset weekly for at least one year and, through collaborations, to develop it further and expand its use. Nature Publishing Group UK 2022-07-23 /pmc/articles/PMC9308035/ /pubmed/35871228 http://dx.doi.org/10.1038/s41597-022-01543-8 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
Nerpel, Afra
Yang, Liuhuaying
Sorger, Johannes
Käsbohrer, Annemarie
Walzer, Chris
Desvars-Larrive, Amélie
SARS-ANI: a global open access dataset of reported SARS-CoV-2 events in animals
title SARS-ANI: a global open access dataset of reported SARS-CoV-2 events in animals
title_full SARS-ANI: a global open access dataset of reported SARS-CoV-2 events in animals
title_fullStr SARS-ANI: a global open access dataset of reported SARS-CoV-2 events in animals
title_full_unstemmed SARS-ANI: a global open access dataset of reported SARS-CoV-2 events in animals
title_short SARS-ANI: a global open access dataset of reported SARS-CoV-2 events in animals
title_sort sars-ani: a global open access dataset of reported sars-cov-2 events in animals
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308035/
https://www.ncbi.nlm.nih.gov/pubmed/35871228
http://dx.doi.org/10.1038/s41597-022-01543-8
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