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SpillOver: A new tool for ranking the risk of viral spillover to humans using big data

Zoë Grange1*, Tracey Goldstein1, Christine K. Johnson1, Simon Anthony2, 3, 4, Kirsten Gilardi1, Peter Daszak4, Kevin J. Olival4, Tammie O'Rourke5, Suzan Murray6, PREDICT Consortium7 and Jonna A. Mazet8
  • 1 One Health Institute, School of Veterinary Medicine, University of California, Davis, United States
  • 2 Center for Infection and Immunity, Mailman School of Public Health, Columbia University Irving Medical Center, United States
  • 3 Department of Epidemiology, Mailman School of Public Health, Columbia University Irving Medical Center, United States
  • 4 EcoHealth Alliance, United States
  • 5 Metabiota, Inc., Canada
  • 6 Smithsonian Conservation Biology Institute (SI), United States
  • 7 One Health Institute, School of Veterinary Medicine, University of California, Davis, United States
  • 8 One Health Institute, School of Veterinary Medicine, University of California, Davis, United States

It is estimated that there are up to 827,000 undiscovered viruses in animals with the potential to spill over into people. Of this large pool, how do we determine which viruses pose the greatest threat to humans? The PREDICT project of the U.S. Agency for International Development (USAID) Emerging Pandemic Threats Program was established in 2009 to build capacity to detect wildlife viruses at high risk disease transmission interfaces in over 30 countries. This and other viral discovery efforts have rapidly expanded our knowledge of the global virome but also raised questions about the risk these viruses pose to humans. A tool is needed to systematically evaluate novel viruses in terms of their zoonotic and pandemic potential. Drawing upon knowledge gained from known zoonotic viruses and the circumstances resulting in their spillover into humans, we have created an interactive web application, called SpillOver: Viral Risk Ranking. By combining a large number of virologic factors alongside environmental and host factors and acquiring a broad scope of expert opinion, our approach is one of the most comprehensive assessments of viral risk. SpillOver ranks viruses from 24 viral families of concern to human health in order of their potential for zoonotic transmission from animals to humans. First, we conducted a survey of 66 international experts in the field of virology, epidemiology, ecology, molecular biology, public health, veterinary and human medicine, and One Health. Each participant ranked risk factors identified as important contributors to viral spillover from no risk to high risk. The viral risk ranking framework applies a weighting scheme to all factors, identified through extensive literature review and research in the field, on the basis of expert opinion on perceived risk; incorporates data from 42 peer reviewed host, environment, and viral risk factors; and calculates an aggregate risk score for each virus. Over 250,000 viral detection records were collated from multiple sources, including a dataset of PREDICT-detected wildlife-origin viruses, NCBI virus nucleotide records, and a literature review of known zoonotic viruses. To date, SpillOver has ranked 686 viruses, including 79 known zoonotic viruses and 475 newly-detected wildlife-origin viruses found during PREDICT. Each risk factor contains categorical or summation factor levels which vary depending on the data source. Data were derived from 19 publicly available resources including: 5 global geospatial datasets for environmental factors, 5 public databases for host biotic factors, and 9 virus peer-reviewed publications or databases. The SpillOver application produces a detailed risk report for each virus. The report details the relative risk of host, viral, and environmental factors that contribute to a virus’ overall spillover risk score. The web-based tool has been developed as a crowd-sourcing platform in which all can collaboratively participate in the collation and ranking of new and existing viruses in the database. The innovative design is fully customizable for future developments, including updating new and existing risk factors and incorporation of newly-developed and updated data sets. SpillOver is intended for an audience of scientists and non-technical users, including policy professionals, virologists, epidemiologists, public and animal health managers, and the general public, especially in countries with higher risk of emerging infectious diseases. We have developed a globally accessible springboard to prompt discussion between scientists and policy makers. By creating a starting point, we attempt to address the burden of uncertainty created by viral discoveries using a scientifically informed process, while identifying targets for further investigation that could lead to public health interventions prior to a zoonotic outbreak, instead of the costly, in both the economic and societal sense, reactionary response we have used to date.

Keywords: virus, emerging infectious disease, wildlife, disease ecology, environment, Human Disease

Conference: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data, Davis, United States, 8 Oct - 10 Oct, 2019.

Presentation Type: Regular oral presentation

Topic: Emerging GIS, data science and sensor technologies adapted to animal, plant and human health, including precision medicine and precision farming

Citation: Grange Z, Goldstein T, Johnson CK, Anthony S, Gilardi K, Daszak P, Olival KJ, O'Rourke T, Murray S, Consortium P and Mazet JA (2019). SpillOver: A new tool for ranking the risk of viral spillover to humans using big data. Front. Vet. Sci. Conference Abstract: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data. doi: 10.3389/conf.fvets.2019.05.00068

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Received: 31 May 2019; Published Online: 27 Sep 2019.

* Correspondence: Dr. Zoë Grange, One Health Institute, School of Veterinary Medicine, University of California, Davis, Davis, United States, zlgrange@ucdavis.edu