A new University of Liverpool study could help scientists mitigate the future spread of zoonotic and livestock diseases caused by viruses.
A new University of Liverpool study could help scientists mitigate the future spread of zoonotic and livestock diseases caused by viruses.
Researchers have used a form or artificial intelligence (AI) called machine-learning to predict more than 20,000 unknown associations between known viruses and susceptible mammalian species. The findings, which are published in Nature Communications, could be used to help target disease surveillance programmes.
Thousands of viruses are known to affect mammals, with recent estimates indicating that less than 1% of mammalian viral diversity has been discovered to date. Some of these viruses such as human and feline immunodeficiency viruses have a very narrow host range, whereas others such as rabies and West Nile viruses have very wide host ranges.
“Host range is an important predictor of whether a virus is zoonotic and therefore poses a risk to humans. Most recently, SARS-CoV-2 has been found to have a relatively broad host range which may have facilitated its spill-over to humans. However, our knowledge of the host range of most viruses remains limited,” explains lead researcher Dr Maya Wardeh from the University’s Institute of Infection, Veterinary and Ecological Sciences.
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Image: Networks of observed and predicted associations between wild and semi-domesticated mammalian hosts and known virus species. (Credit: Dr. Maya Wardeh)
