Evidence map›Paper›PMID 35871228›Full record

ArticleScientific data2022

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

Afra Nerpel, Liuhuaying Yang, Johannes Sorger, Annemarie Käsbohrer, Chris Walzer, Amélie Desvars-Larrive

Abstract readDataset
In one paragraph

Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Monitoring for respiratory viruses among wild canids, Texas.One health (Amsterdam, Netherlands) · 2025
    Article
  7. Pathogens and planetary change.Nature reviews. Biodiversity · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Data on SARS-CoV-2 events in animals: Mind the gap!One health (Amsterdam, Netherlands) · 2023
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Oral Sampling of Little Brown BatAnimals : an open access journal from MDPI · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Afra NerpelUnit of Veterinary Public Health and Epidemiology, University of Veterinary Medicine Vienna, Veterinaerplatz 1, 1210, Vienna, Austria.ORCID 0000-0001-8381-3610
Liuhuaying YangComplexity Science Hub Vienna, Josefstaedter Strasse 39, 1080, Vienna, Austria.ORCID 0000-0003-1279-4736
Johannes SorgerComplexity Science Hub Vienna, Josefstaedter Strasse 39, 1080, Vienna, Austria.ORCID 0000-0002-5212-8941
Annemarie KäsbohrerUnit of Veterinary Public Health and Epidemiology, University of Veterinary Medicine Vienna, Veterinaerplatz 1, 1210, Vienna, Austria.
Chris WalzerWildlife Conservation Society, 2300 Southern Blvd, Bronx, NY, 10460, USA.
Amélie Desvars-LarriveUnit of Veterinary Public Health and Epidemiology, University of Veterinary Medicine Vienna, Veterinaerplatz 1, 1210, Vienna, Austria. amelie.desvars@vetmeduni.ac.at.ORCID 0000-0001-7671-696X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 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.

Indexed as

Animal DiseasesCOVID-19SARS-CoV-2AnimalsHumans

Identifiers

PMID35871228
PMCPMC9308035

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.