Researchers have developed network-based models to rank new and well-known viruses according to their ability to spread infectious diseases through animals, that is, between humans and animals.
The discovery was published in the journal Communication Biology.
New Virus Priority
Machine learning models conclude that more species can serve as hosts for new coronaviruses. This finding indicates that coronavirus surveillance should be a priority.
To quantify the risk of animal-to-human transmission, the researchers assigned each virus a priority score.
Lead author and veterinary epidemiologist Pranav Pandit, a UC Davis One Health Institute researcher.
The link between environmental change and viruses
The model calculates the probability that humans will act as hosts for more than 500 new viruses identified between 2009 and 2019. It does this by using a data-driven network of virus-hosted servers. .
Insights into virus and host ecology have been provided through host-pathogen networks. This information is important to determine the risk the virus poses to human health. It is especially important when considering environmental and climate changes. The risk of virus transmission between species may increase as landscapes change and species adapt and relocate in response.
“This study shows how different wildlife species are connected by the viruses they share. Environmental change is a big driver for species to move around. How viruses interact Working with different hosts in a changing environment is crucial to understanding the risk they pose to human health,” said corresponding author Christine Johnson, professor of epidemiology and health. ecosystem of UC Davis and director of EpiCenter for Disease Dynamics.
The machine learning model compared multiple paramyxoviruses with coronaviruses. It is a top priority for future research. Measles, mumps and respiratory infections are among the diseases brought about by this family of viruses.
“Characterization of hundreds of viruses is time-consuming and requires prioritization,” said Pandit. Our network-based method helps identify early signals in ecological trajectories and evolution of these viruses. It may also help unravel the missing links between viruses and their hosts.” .