Study predicts the next human virus from mammals

Man sells bats in a market at a village near Kikwit
Copyright: Panos

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  • Researchers created database having 2,805 mammal–virus associations
  • They identified bats as having more viruses likely to infect humans
  • But expert suggests need to explore how insect vectors spread viruses

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[KAMPALA] A study has suggested that scientists could predict where on the planet the next virus could jump from animals to humans, thus providing data that will aid in early warning systems and disease surveillance efforts.
According to the US-based researchers, few analytical tools exist to help scientists understand the patterns of viral diversity in wildlife and how these may successfully become the next human virus, or which viruses could cross species boundaries.
The study published last month (21 June) in the Nature journal helps build a roadmap of where to prioritise disease surveillance efforts around the world to better stop viruses from having a large impact.
In the study, the scientists have mapped out the ‘missing zoonoses’ giving geographic hotspots as eastern, central and southern Africa, South and Central America as well as parts of Asia.

“We want to get ahead of the curve, and be able to develop early warning systems to identify and find emerging disease threats.”

Kevin J. Olival, EcoHealth Alliance


‘Missing zoonoses’ are the number of predicted zoonotic viruses per mammal species minus the number of zoonotic viruses  already known for that species. Hotspots are locations on the planet likely to be the source of the next emerging, zoonotic diseases and they varry across different groups of mammals.
Scientists analysed major online databases such as PubMed and Google Scholar for articles published between 1940 and 2015 for zoonotic viruses — those known to have been detected in humans and at least one other mammalian host. They also reviewed books, reviews, and literature cited in sources of the identified articles.
They created a database of 2,805 mammal–virus associations to build mathematical models that allowed them to identify which species traits and groups of mammals carry the largest numbers of viruses and the virus traits that make some viruses more likely to jump into humans.
For instance, they demonstrated that bats harbour a significantly higher proportion of zoonotic viruses than all other mammals.
“We want to get ahead of the curve, and be able to develop early warning systems to identify and find emerging disease threats before or soon after they emerge in the human population,” says Kevin J. Olival, the principal investigator and an associate vice-president for research for US-based EcoHealth Alliance, which conducted the study.
“These show which are the predicted number of viruses that are out there, minus what we already know exist. We also identify virus traits that make some viruses more likely to jump into humans versus others.”
Olival adds that their data is already in use as part of a project to find and characterize new viruses around the world, and to better understand the location-specific risk factors and human behaviours in zoonotic virus hotspots.
Ritah Nakayinga, a lecturer of virology at the International Health Sciences University in Uganda, tells SciDev.Net that the study showed that classes of mammals such as primates and rodents have a higher proportion of zoonotic virus, which is an interesting finding and is supported by the Ebola and Marburg outbreaks in the world and Uganda respectively.

“Although much of the study focused on reservoir mammals, exploration into insect vectors would throw light on spillover events which are the basis of recent outbreaks [such as] Zika, Chikugunya and yellow fever,” Nakayinga explains
Nakayinga, who is also a zoonotic researcher, notes that most disease outbreaks in Africa have originated from bats, rodents and mosquitoes but the study’s findings show that cows, primates and carnivores are highest mammal proportions in Africa and that viruses they harbour could potentially be zoonotic.
“This raises questions on methodologies used to conclude this,” says Nakayinga. “It goes to show that literature-based databases for establishment of models may not be appropriate tool for making predictions although they may be preferred because of costs implications.”
This piece was produced by SciDev.Nets Sub-Saharan Africa English desk.


Kevin J. Olival and others Host and viral traits predict zoonotic spillover from mammals (Nature, 21 June 2017)