SARS-ANI: A Global Open Access Dataset of Reported SARS-CoV-2 Events in Animals

Abstract

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 animal hosts. We used two major health databases to extract unstructured data and generated a comprehensive global dataset of thoroughly documented SARS-CoV-2 events in animals. The dataset 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 adapt monitoring strategy, prevent the formation of animal reservoirs, and tailor 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 collaborative processes, to develop the dataset further and expand its use.