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Novel coronaviruses are riskiest for spillover

Novel coronaviruses are riskiest for spillover
A wildlife surveillance team member samples a bumblee bat for viruses in Myanmar. Credit: Smithsonian Conservation Biology Institute

Previously decade, scientists have described a huge selection of novel viruses with the potential to pass between wildlife and humans. But how do they know which are riskiest for spillover and for that reason 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 his or her threat of zoonotic transmission, that is when pass between animals and humans.

Their study, published in the journal Communications Biology, provides further evidence that coronaviruses are riskiest for spillover and really should continue being prioritized for enhanced surveillance and research.

The device learning models were created by the EpiCenter for Disease Dynamics at the UC Davis One Health Institute in the institution of Veterinary Medicine.

Prioritizing novel viruses

The models discovered that novel viruses from the coronavirus family are anticipated to possess a larger amount of species as hosts. That is in keeping with known viruses, indicating this category of viruses ought to be most highly prioritized for surveillance.

The scientists created a prioritization score for every virus to serve as a metric for the chance of zoonotic transmission.

“As surveillance expands, hopefully to be inundated with data connected with viruses,” said lead author and veterinary epidemiologist Pranav Pandit, a researcher with the UC Davis One Health Institute. “These tools can help us understand the chance from , that may help plan future pandemics.”

Novel coronaviruses are riskiest for spillover
This illustration represents a host-pathogen network model developed by UC Davis researchers. It shows potential linkages between 531 novel and known viruses, with different colors representing different virus families. Credit: UC Davis

Environmental change and viral connections

The model runs on the data-driven, virus-host network to quantify the probability of humans as hosts for a lot more than 500 viruses newly discovered between 2009 and 2019. This stemmed from wildlife surveillance research conducted in Africa, Asia and Latin America by way of a consortium of investigators.

Host-pathogen networks provide insight in to the ecology of viruses and their hosts, that is critical to understanding the chance such viruses pose to human health. That is especially important amid a changing climate and environment. Because the landscape changes and species shift and move around in response, the chance of viral transmission across species can increase.

“This study shows how different wildlife species are connected by the viruses they share,” said corresponding author Christine Johnson, a UC Davis professor of epidemiology and ecosystem health insurance and director of the EpiCenter for Disease Dynamics. “Environmental change is really a massive driver for moving species around. How viruses connect to different hosts in a changing environment is crucial to understanding the chance they pose to .”

High priorities

In additional to coronaviruses, the model also ranked several paramyxoviruses as high priorities for future work. Diseases connected with this category of viruses include measles, mumps and respiratory system infections.

“Characterizing a huge selection of viruses requires a large amount of time and requires prioritization,” Pandit said. “Our network-based approach helps identify the first signals in the ecological and evolutionary trajectories of the viruses. Additionally, it may help illuminate missing links between and their hosts.”

More info: P. S. Pandit et al, Predicting the prospect of zoonotic transmission and host associations for novel viruses, Communications Biology (2022). DOI: 10.1038/s42003-022-03797-9

Citation: Novel coronaviruses are riskiest for spillover (2022, August 25) retrieved 26 August 2022 from

This document is at the mercy of copyright. Aside from any fair dealing for the intended purpose of private study or research, no part could be reproduced minus the written permission. This content is provided for information purposes only.

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