By running data on flavivirus-positive species through a machine-learning model of known mammal and bird species, scientists from the University of California, Davis (UC Davis) believe they have honed in on those animals most likely to host future flaviviruses.
Flavivirus refers to troublesome viruses such as Zika, West Nile and dengue fever. They are epidemic capable and frequently widespread in their damage. Often they are spread by mosquitoes and ticks, but with more than 10,000 avian and 5,000 mammal species out there, predicting what creature might next bear their contagion can be a dubious prospect, which is what makes these scientists findings — published in the journal Nature Communications — so impactful.
“Tomorrow, if there’s an outbreak anywhere in the world, we now know which wildlife species are most likely to be infected in addition to humans,” said Pranav Pandit, lead author and a postdoctoral scholar with the UC Davis One Health Institute’s EpiCenter for Disease Dynamics in the School of Veterinary Medicine.
The findings could help more than just humans, though. As UC Davis professor and co-leading author Christine Kreuder Johnson explained, primates, in general, can benefit — as well as from the noninvasive sampling techniques the UC Davis One Health Institute used for the study.
“We needed this modeling technique to help us understand the most likely hosts for these viruses in their natural habitat,” Johnson said. “That’s important for both global health and wildlife conservation. Many of these primates are already endangered, and these diseases burden an already strained population.”