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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 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.


Afra Nerpel, Liuhuaying Yang, Johannes Sorger, Annemarie Käsbohrer, Chris Walzer, Amélie Desvars-Larrive, SARS-ANI: a global open access dataset of reported SARS-CoV-2 events in animals, Scientific Data 9 (438) (2022)

Liuhuaying Yang, faculty member at the Complexity Science Hub

Liuhuaying Yang

Johannes Sorger

Amelie Desvars-Larrive, Faculty Member at the Complexity Science Hub © Verena Ahne

Amélie Desvars-Larrive

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