Ranking the risk of animal-to-human spillover for newly discovered viruses
Edited by Jonathan Dushoff, McMaster University, Hamilton, ON, Canada, and accepted by Editorial Board Member Simon A. Levin February 8, 2021 (received for review February 12, 2020)
Correction
September 20, 2021
Significance
The recent emergence and spread of zoonotic viruses, including Ebola virus and severe acute respiratory syndrome coronavirus 2, demonstrate that animal-sourced viruses are a very real threat to global public health. Virus discovery efforts have detected hundreds of new animal viruses with unknown zoonotic risk. We developed an open-source risk assessment to systematically evaluate novel wildlife-origin viruses in terms of their zoonotic spillover and spread potential. Our tool will help scientists and governments assess and communicate risk, informing national disease prioritization, prevention, and control actions. The resulting watchlist of potential pathogens will identify targets for new virus countermeasure initiatives, which can reduce the economic and health impacts of emerging diseases.
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.
Data Availability
All datasets along with the R code and R package dependencies needed to fully replicate and evaluate these analyses have been deposited in Open Source Framework (https://osf.io/mb6qn/?view_only=f6326d48d7d941afa7af02714819a1a2) (33).
Acknowledgments
We thank P. Pandit and C. Zambrana-Torellio for analytical support and D. Carroll, A. Clements, and Murray Trostle for their vision and support. This study was made possible by the generous support of the American people through US Agency for International Development (USAID) Emerging Pandemic Threats PREDICT Project Awards GHN-A-00-09-00010-00 and AID-OAA-A-14-00102. USAID had no involvement in the design and content of this manuscript. The contents of this manuscript and associated materials are the responsibility of the authors and do not necessarily reflect the views of USAID or the US Government.
Supporting Information
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Copyright © 2021 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
Data Availability
All datasets along with the R code and R package dependencies needed to fully replicate and evaluate these analyses have been deposited in Open Source Framework (https://osf.io/mb6qn/?view_only=f6326d48d7d941afa7af02714819a1a2) (33).
Submission history
Published online: April 5, 2021
Published in issue: April 13, 2021
Change history
September 16, 2021: The text of this article and SI Appendix have been updated; please see accompanying Correction for details.
Keywords
Acknowledgments
We thank P. Pandit and C. Zambrana-Torellio for analytical support and D. Carroll, A. Clements, and Murray Trostle for their vision and support. This study was made possible by the generous support of the American people through US Agency for International Development (USAID) Emerging Pandemic Threats PREDICT Project Awards GHN-A-00-09-00010-00 and AID-OAA-A-14-00102. USAID had no involvement in the design and content of this manuscript. The contents of this manuscript and associated materials are the responsibility of the authors and do not necessarily reflect the views of USAID or the US Government.
Notes
This article is a PNAS Direct Submission. J.D. is a guest editor invited by the Editorial Board.
3The complete lists of Expert Panel and PREDICT Consortium can be found in SI Appendix.
See online for related content such as Commentaries.
Authors
Competing Interests
The authors declare no competing interest.
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Ranking the risk of animal-to-human spillover for newly discovered viruses, Proc. Natl. Acad. Sci. U.S.A.
118 (15) e2002324118,
https://doi.org/10.1073/pnas.2002324118
(2021).
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