文章基本信息

标题：SARS-ANI: a global open access dataset of reported SARS-CoV-2 events in animals
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作者：afra Nerpel ; LiuhuayingYang ; Johannes Sorger 等
期刊名称：Scientific Data
电子版ISSN：2052-4463
出版年度：2022
卷号：9
期号：1
页码：1-13
DOI：10.1038/s41597-022-01543-8
语种：English
出版社：Nature Publishing Group
摘要：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 fexibility of the data will support research eforts 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 .