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Ranking the risk of animal-to-human spillover for newly discovered viruses

Grange, Zoë L., Goldstein, Tracey, Johnson, Christine K., Anthony, Simon, Gilardi, Kirsten, Daszak, Peter, Olival, Kevin J., O'Rourke, Tammie, Murray, Suzan, Olson, Sarah H., Togami, Eri, Vidal, Gema, Mazet, Jonna A. K. and Goossens, Benoit 2021. Ranking the risk of animal-to-human spillover for newly discovered viruses. Proceedings of the National Academy of Sciences 118 (15) , e2002324118. 10.1073/pnas.2002324118

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Abstract

The death toll and economic loss resulting from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic are stark reminders that we are vulnerable to zoonotic viral threats. Strategies are needed to identify and characterize animal viruses that pose the greatest risk of spillover and spread in humans and inform public health interventions. Using expert opinion and scientific evidence, we identified host, viral, and environmental risk factors contributing to zoonotic virus spillover and spread in humans. We then developed a risk ranking framework and interactive web tool, SpillOver, that estimates a risk score for wildlife-origin viruses, creating a comparative risk assessment of viruses with uncharacterized zoonotic spillover potential alongside those already known to be zoonotic. Using data from testing 509,721 samples from 74,635 animals as part of a virus discovery project and public records of virus detections around the world, we ranked the spillover potential of 887 wildlife viruses. Validating the risk assessment, the top 12 were known zoonotic viruses, including SARS-CoV-2. Several newly detected wildlife viruses ranked higher than known zoonotic viruses. Using a scientifically informed process, we capitalized on the recent wealth of virus discovery data to systematically identify and prioritize targets for investigation. The publicly accessible SpillOver platform can be used by policy makers and health scientists to inform research and public health interventions for prevention and rapid control of disease outbreaks. SpillOver is a living, interactive database that can be refined over time to continue to improve the quality and public availability of information on viral threats to human health.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Biosciences
Additional Information: Benoit Goossens contributed as a member of the Predict Consortium. This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
Publisher: National Academy of Sciences
ISSN: 0027-8424
Date of First Compliant Deposit: 4 October 2021
Date of Acceptance: 5 April 2021
Last Modified: 14 Dec 2021 13:00
URI: https://orca.cardiff.ac.uk/id/eprint/144620

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