Questions and Answers: New tool rates viruses according to their risk of jumping to people


W.Before the world grappled with the COVID-19 pandemic, researchers were already looking for possible outbreaks of emerging diseases – and trying to stop them. A major hurdle here is understanding which viruses in animals are most likely to make the leap to humans. A new, interactive web-based tool released on April 5th in PNASuses 32 risk factors and data on more than 500,000 samples from nearly 75,000 animals, as well as public records of virus detections in wildlife, to rank the likelihood of an overflow among 887 viruses.

Project leader Jonna Mazet, epidemiologist and disease ecologist at the University of California’s Davis School of Veterinary Medicine, spoke with The scientist via the “SpillOver” tool that you and your employees have developed.

The scientist: Tell me how this project started.

Jonna Mazet

UC DaVIS

Jonna Mazet: For more than a decade, I’ve been the PI and head of the PREDICT Consortium, a very large group of scientists, laboratory technicians, and health professionals working in more than 35 countries around the world to strengthen systems for identifying viruses that are Having previously identified viruses of concern they are overflowing and making people sick. In doing so, we strengthened the systems, but also discovered viruses, and we wanted to inform the political decision-makers about the risk of the viruses found and give them some information.

I think we were a little surprised and disappointed that there wasn’t good information in the scientific literature on how to really rank these viruses. So we had to start this effort when we set up the systems and discovered viruses. This is a high point of this huge collaborative project, in which at least 400 people from the PREDICT project as well as experts from around the world in the fields of virology, ecology, epidemiology and other disciplines took part.

TS: How did you create the SpillOver tool and how does it work?

JM: We have conducted intensive literature research and, if you will, also examined the minds of the scientists and individuals working on the PREDICT project. And then we put together all of the risk factors that we could identify as. . . Risk bits in all scientific publications that have talked about and even spread about the risk of virus overflows. . . . We added those that we found in the PREDICT project as most of what we could find in the literature dealt only with virology and did not include the host, the environmental risk component for exposure, or any of the ecology. . . . And then we reached out to scientists around the world who had worked at the forefront of their fields in this particular area of ​​zoonosis, virology and spillovers and asked them to rank the risk factors we identified and their priorities.

For example, if a virologist has classified one of the virology-related risk factors, he can rate himself as an expert. But if you looked at one that is more in the field of ecology, you might consider yourself a little lower in your expertise. And we use their rankings, as well as their self-assigned expertise, to then examine all of the risk factors and put together a program – basically equations – to get a weighted score for each risk factor. And then we used that to find the data for all known zoonoses that were first found in wildlife and broadcast to humans as a kind of gut test of our ranking system to see if it was working. And then when we found out that the historical overflow tool seemed to work very well, we classified the viruses that the PREDICT project found.

See “Predicting Future Zoonotic Outbreaks”

TS: Where was SARS-CoV-2?

JM: When we first worked on it, there was obviously no SARS-CoV-2 that we knew about – it existed, but it hadn’t been identified yet. At first it wasn’t even in our system, but when we wanted to finalize the manuscript and tool, we added SARS-CoV-2. . . with all the other viruses that came out in the literature and in GenBank and GISAID and others.

When we added SARS-CoV-2 it was number two known zoonotics -[second to Lassa virus, found among rodents in West Africa and which causes hemorrhagic fever in people]. This is a ranking for its ability and likelihood to spill over again, and it does hint a bit about the pandemic potential of our risk ranking system. And I find that very instructive. . . . Obviously, it is a terrible virus that caused the pandemic. Therefore it should have a very high priority. And the reason it doesn’t rank even higher than number one is because it wasn’t examined until it overflowed.

Our goal is to actually evaluate and test viruses before they overflow so that we can place them on a watchlist, so that countries with these viruses can create watchlists and do monitoring and mitigation before they overflow. As more information comes out about the host and distribution of SARS-CoV-2 – it is obviously in humans worldwide, but we are interested in its distribution in wildlife and the potential reservoir hosts – I think it could go even further Number one.

ZL Grange et al., “Animal-to-Human Overflow Risk Assessment for Newly Discovered Viruses”. PNAS118, e2002324118, 2021.

Editor’s Note: This interview has been edited for brevity.



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