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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...
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/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. |
format | Online Article Text |
id | pubmed-9308035 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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