ArticleOne health (Amsterdam, Netherlands)2023
Data on SARS-CoV-2 events in animals: Mind the gap!
Article in One health (Amsterdam, Netherlands), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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.
Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
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- Article
- Four Novel SARS-CoV-2 Infected Feral American Mink (Animals : an open access journal from MDPI · 2025Article
- Agriculture data sharing review.Heliyon · 2025Article
- Investigating SARS-CoV-2 Neutralising Antibody Response in Sheep.Microorganisms · 2024Article
- Higher Frequency of SARS-CoV-2 RNA Shedding by Cats than Dogs in Households with Owners Recently Diagnosed with COVID-19.Viruses · 2024Article
- Whole-genome sequencing of SARS-CoV-2 from the initial cases of domestic cat infections in Canada.Microbiology resource announcements · 2024Article
- Safety and immunogenicity of a SARS-CoV-2 mRNA vaccine (SYS6006) in minks, cats, blue foxes, and raccoon dogs.Frontiers in cellular and infection microbiology · 2024Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Current research on SARS-CoV-2 has largely focused on the pandemic's impact on humans, with insufficient attention paid to monitoring, sharing, and communicating information about viral circulation and evolution in animal hosts. The objective of this study was to estimate and characterise the data gap between the number of SARS-CoV-2 cases and related deaths in animals officially notified to the World Organisation for Animal Health (WOAH) via its World Animal Health Information System (WAHIS) and known cases reported through two other data sources: ProMED-mail and scientific papers. We used the previously published dataset SARS-ANI to retrieve SARS-CoV-2 events in animals published through WAHIS and ProMED-mail. Additionally, we generated SARS-ANI SciLit v1.0, a novel structured dataset of SARS-CoV-2 events in animals published through scientific literature retrieved from PubMed. We evidenced that at least 52.8% of the SARS-CoV-2 animal cases and 65.8% of the deaths were not reported to WAHIS during 29/02/2020-16/08/2022. Combining information from three different data sources, we compiled a new comprehensive list of 35 animal species reported as susceptible to SARS-CoV-2 under natural conditions, representing a significant advance from the figures reported by the WOAH and the Food and Agriculture Organization of the United Nations. Furthermore, we identified animal species that were underreported to the WAHIS and found that dogs and cats garnered the most attention in research studies. We also showed that, compared to the official WAHIS reports, scientific papers generally experienced longer publication lags and demonstrated that national strategies regarding reporting/publishing of SARS-CoV-2 events in animals greatly differed among countries. This analysis provides valuable insights into the patterns of reporting animal infections with SARS-CoV-2. The study emphasises the need for improvements in data sharing regarding SARS-CoV-2 events in animals, as this is crucial for effective One Health surveillance, prevention, and control of emerging diseases of zoonotic origin.
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Registered trials
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.