Zoonotic Risk Technology Enters the Viral Emergence Toolkit

Colin Carlson; Maxwell Farrell; Zoe Grange; Barbara Han; Nardus Mollentze; Alexandra Phelan; Angela Rasmussen; Gregory Albery; Bernard Bett; David Brett-Major; Lily Cohen; Tad Dallas; Evan Eskew; Anna Fagre; Kristian Forbes; Rory Gibb; Sam Halabi; Charlotte Hammer; Rebecca Katz; Jason Kindrachuk; Renata Muylaert; Felicia Nutter; Joseph Ogola; Kevin Olival; Michelle Rourke; Sadie Ryan; Noam Ross; Stephanie Seifert; Tarja Sironen; Claire Standley; Kishana Taylor; Marietje Venter; Paul Webala

doi:10.20944/preprints202104.0200.v1

How to cite: Carlson, C.; Farrell, M.; Grange, Z.; Han, B.; Mollentze, N.; Phelan, A.; Rasmussen, A.; Albery, G.; Bett, B.; Brett-Major, D.; Cohen, L.; Dallas, T.; Eskew, E.; Fagre, A.; Forbes, K.; Gibb, R.; Halabi, S.; Hammer, C.; Katz, R.; Kindrachuk, J.; Muylaert, R.; Nutter, F.; Ogola, J.; Olival, K.; Rourke, M.; Ryan, S.; Ross, N.; Seifert, S.; Sironen, T.; Standley, C.; Taylor, K.; Venter, M.; Webala, P. Zoonotic Risk Technology Enters the Viral Emergence Toolkit. Preprints 2021, 2021040200. https://doi.org/10.20944/preprints202104.0200.v1. Carlson, C.; Farrell, M.; Grange, Z.; Han, B.; Mollentze, N.; Phelan, A.; Rasmussen, A.; Albery, G.; Bett, B.; Brett-Major, D.; Cohen, L.; Dallas, T.; Eskew, E.; Fagre, A.; Forbes, K.; Gibb, R.; Halabi, S.; Hammer, C.; Katz, R.; Kindrachuk, J.; Muylaert, R.; Nutter, F.; Ogola, J.; Olival, K.; Rourke, M.; Ryan, S.; Ross, N.; Seifert, S.; Sironen, T.; Standley, C.; Taylor, K.; Venter, M.; Webala, P. Zoonotic Risk Technology Enters the Viral Emergence Toolkit. Preprints 2021, 2021040200. https://doi.org/10.20944/preprints202104.0200.v1.

Abstract

In light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programs will identify hundreds of novel viruses that might someday pose a threat to humans. Our capacity to identify which viruses are capable of zoonotic emergence depends on the existence of a technology—a machine learning model or other informatic system—that leverages available data on known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions: What are the prerequisites, in terms of open data, equity, and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it, and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges?

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Zoonotic Risk Technology Enters the Viral Emergence Toolkit

Abstract

Keywords

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