Video-tracking the effect of influenza infection on ferrets
A guest blogpost by Ding Yuan Oh, PhD
Conventional ferret activity measurements by human observation
Ferrets are the ideal animal model to assess influenza virus infection and pathogenicity as they display similar clinical symptoms to humans such as sneezing, fever and lethargy. Conventionally, lethargy or ferret activity is determined manually by an observer. However, this method is prone to bias and requires trained personnel to recognise subtle changes in individual ferret activity.
Simple and less subjective method by video-tracking
We assessed the usefulness of EthoVision XT as an alternative method to measure ferret activity throughout the course of influenza virus infection. We utilise mobility measurements such as activity, distance and velocity in EthoVision XT as a read-out of the ‘activity level’ of ferrets.
In contrast to the conventional manual observation method, video-tracking by EthoVision XT proved to be a more sensitive method in detecting a reduction in ferret activity level after influenza infection. Not only does video-tracking provide greater detection sensitivity, it also simplifies the process of activity measurement by eliminating the reliance on trained personnel and being less subjective than the conventional method.
Wide application to other ferret model of infection
Our study is the first to use video-tracking to monitor the activity of ferrets. The ferret is a widely used animal model for studying influenza infection and is beginning to be adopted as a model for other infectious viruses such as Hendra virus, Nipah virus and SARS-CoV. Therefore, we anticipate that this improved method could be used to study both the pathogenesis of different viruses and the effectiveness of existing and novel therapeutic interventions in a ferret model.
Read more in the complete study:
Oh, D.Y.; Barr, I.G.; Hurt, A.C. (2015). A Novel Video Tracking Method to Evaluate the Effect of Influenza Infection and Antiviral Treatment on Ferret Activity. PLoS ONE, 10(3): e0118780.
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