In the past decade, scientists have described hundreds of novel viruses with the potential to pass between wildlife and humans. But how can they know which are riskiest for spillover and therefore which to prioritize for further surveillance in people?
August 25, 2022
In the past decade, scientists have described hundreds of novel viruses with the potential to pass between wildlife and humans. But how can they know which are riskiest for spillover and therefore which to prioritize for further surveillance in people?
Scientists from the University of California, Davis created network-based models to prioritize novel and known viruses for their risk of zoonotic transmission, which is when infectious diseases pass between animals and humans.
Their study, published in the journal Communications Biology, provides further evidence that coronaviruses are riskiest for spillover and should continue to be prioritized for enhanced surveillance and research.
The machine learning models were designed by the EpiCenter for Disease Dynamics at the UC Davis One Health Institute in the School of Veterinary Medicine.
Prioritizing novel viruses
The models found that novel viruses from the coronavirus family are expected to have a larger number of species as hosts. This is consistent with known viruses, indicating this family of viruses should be most highly prioritized for surveillance.
