Literature detail

SARS-ANI: a global open access dataset of reported SARS-CoV-2 events in animals.

Afra Nerpel1 Liuhuaying Yang2 Johannes Sorger2 Annemarie Käsbohrer1 Chris Walzer3,4 Amélie Desvars-Larrive5,6,7
Affiliations 7 institutions
  1. Unit of Veterinary Public Health and Epidemiology, University of Veterinary Medicine Vienna, Veterinaerplatz 1, 1210, Vienna, Austria.
  2. Complexity Science Hub Vienna, Josefstaedter Strasse 39, 1080, Vienna, Austria.
  3. Wildlife Conservation Society, 2300 Southern Blvd, Bronx, NY, 10460, USA.
  4. Research Institute of Wildlife Ecology, University of Veterinary Medicine Vienna, Savoyenstrasse 1, 1160, Vienna, Austria.
  5. Unit of Veterinary Public Health and Epidemiology, University of Veterinary Medicine Vienna, Veterinaerplatz 1, 1210, Vienna, Austria. [email protected].
  6. Complexity Science Hub Vienna, Josefstaedter Strasse 39, 1080, Vienna, Austria. [email protected].
  7. VetFarm, University of Veterinary Medicine Vienna, Kremesberg 13, 2563, Pottenstein, Austria. [email protected].
PMID 35871228 2022 Sci Data eng epublish
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Article

Publication summary

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.

Animal Diseases COVID-19 SARS-CoV-2 Animals Humans

Structured evidence records

Evidence records

2 total
1 records
Extraction confidence 0.75
Key finding

A global dataset of SARS-CoV-2 events in animals was created to support research on animal reservoirs and their ecological context.

Virus
Host
Location
Supporting text

We used two major health databases to extract unstructured data and generated a global dataset of SARS-CoV-2 events in animals. 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.

Method
data extraction; database compilation
Geographic raw
global
1 records
Extraction confidence 0.95
Key finding

A global dataset was compiled collating SARS-CoV-2 infection events across multiple animal species for ongoing surveillance of viral occurrences in animals.

Virus
Host
Location
Supporting text

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.

Method
database mining; data harmonization
Geographic raw
global