An aggregated dataset of serial morbidity and titer measurements from influenza A virus-infected ferrets

Autor: Troy J. Kieran, Xiangjie Sun, Hannah M. Creager, Terrence M. Tumpey, Taronna R. Maines, Jessica A. Belser
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Scientific Data, Vol 11, Iss 1, Pp 1-5 (2024)
Druh dokumentu: article
ISSN: 2052-4463
DOI: 10.1038/s41597-024-03256-6
Popis: Abstract Data from influenza A virus (IAV) infected ferrets provides invaluable information towards the study of novel and emerging viruses that pose a threat to human health. This gold standard model can recapitulate many clinical signs of infection present in IAV-infected humans, support virus replication of human, avian, swine, and other zoonotic strains without prior adaptation, and permit evaluation of virus transmissibility by multiple modes. While ferrets have been employed in risk assessment settings for >20 years, results from this work are typically reported in discrete stand-alone publications, making aggregation of raw data from this work over time nearly impossible. Here, we describe a dataset of 728 ferrets inoculated with 126 unique IAV, conducted by a single research group under a uniform experimental protocol. This collection of morbidity, mortality, and viral titer data represents the largest publicly available dataset to date of in vivo-generated IAV infection outcomes on a per-ferret level.
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