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 .
