Researchers developed network-based models to rank new and well-known viruses according to the likelihood of spreading infectious illnesses zoonotically i.e., between people and animals.
This discovery is published in the journal Communications Biology.
Prioritizing New Viruses
The machine learning models concluded that more species might serve as hosts for new coronaviruses. This finding indicates that surveillance of coronaviruses should be prioritized.
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To quantify the risk of zoonotic transmission, the researchers assigned each virus a priority score.
“As surveillance expands, we hope to be inundated with data associated with viruses. These tools will help us understand the risk from novel viruses, which can help prepare for future pandemics,” said lead author and veterinary epidemiologist Pranav Pandit, a researcher with the UC Davis One Health Institute.
Connections Between Environmental Change and Viruses
The model calculates the probability that humans will serve as hosts for more than 500 newly identified viruses between 2009 and 2019. It does this by using a data-driven virus-host network.
Insight into the ecology of viruses and hosts has been provided via host-pathogen networks. This information is crucial for determining the risk that viruses bring to human health. It is particularly critical considering the environmental and climatic changes. The danger of viral transmission between species can rise as the landscape changes 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 massive driver for moving species around. How viruses interact with different hosts in a changing environment is critical to understanding the risk they pose to human health,” said corresponding author Christine Johnson, a UC Davis professor of epidemiology and ecosystem health and director of the EpiCenter for Disease Dynamics.
The machine learning model compared numerous paramyxoviruses with coronaviruses. It was a top priority for future research. Measles, mumps and respiratory tract infections are among the illnesses brought on by this viral family.
“Characterizing hundreds of viruses takes a lot of time and requires prioritization. Our network-based approach helps identify the early signals in the ecological and evolutionary trajectories of these viruses. It can also help illuminate missing links between viruses and their hosts,” said Pandit.
Source: Eurekalert
