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An aggregated dataset of serially collected influenza A virus morbidity and titer measurements from virus-infected ferrets.

Metadata Updated: June 27, 2024

Data from influenza A virus (IAV) infected ferrets (Mustela putorius furo) provides invaluable information towards the study of novel and emerging viruses that pose a threat to human health. This gold standard animal model can recapitulate many clinical signs of infection present in IAV-infected humans, support virus replication of human and 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 (NCIRD/ID/IPB/Pathogenesis Laboratory Team) 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-individual ferret level.

Published Data Descriptor for more information: Kieran TJ, Sun X, Creager HM, Tumpey TM, Maine TR, Belser JA. 2024. An aggregated dataset of serial morbidity and titer measurements from influenza A virus-infected ferrets. Sci Data 11, 510. https://doi.org/10.1038/s41597-024-03256-6

Additional publications using and describing data: Kieran TJ, Sun X, Maines TR, Beauchemin CAA, Belser JA. 2024. Exploring associations between viral titer measurements and disease outcomes in ferrets inoculated with 125 contemporary influenza A viruses. J Virol98:e01661-23.https://doi.org/10.1128/jvi.01661-23

Belser JA, Kieran TJ, Mitchell ZA, Sun X, Mayfield K, Tumpey TM, Spengler JR, Maines TR. 2024. Key considerations to improve the normalization, interpretation and reproducibility of morbidity data in mammalian models of viral disease. Dis Model Mech; 17 (3): dmm050511. doi: https://doi.org/10.1242/dmm.050511

Kieran TJ, Sun X, Maines TR, Belser JA. (Under Review). Machine learning approaches for influenza A risk assessment: identifying predictive correlates using ferret model in vivo data. Communications Biology.

Access & Use Information

Public: This dataset is intended for public access and use. License: See this page for license information.

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Dates

Metadata Created Date January 19, 2024
Metadata Updated Date June 27, 2024

Metadata Source

Harvested from Healthdata.gov

Additional Metadata

Resource Type Dataset
Metadata Created Date January 19, 2024
Metadata Updated Date June 27, 2024
Publisher Centers for Disease Control and Prevention
Maintainer
Identifier https://data.cdc.gov/api/views/cr56-k9wj
Data First Published 2024-04-08
Data Last Modified 2024-05-17
Category National Center for Immunization and Respiratory Diseases
Public Access Level public
Bureau Code 009:20
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://healthdata.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id e7c7cb8e-74ad-4523-820b-27205ea0588e
Harvest Source Id 651e43b2-321c-4e4c-b86a-835cfc342cb0
Harvest Source Title Healthdata.gov
Homepage URL https://data.cdc.gov/d/cr56-k9wj
License https://www.usa.gov/government-works
Program Code 009:026
Source Datajson Identifier True
Source Hash 2267cf1e7c7bd50537d448ee9c7fc05f424d247b84112f7a4e5662c213e30372
Source Schema Version 1.1

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