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The science of the host–virus network

Published

Author(s)

Gregory Albery, Daniel J. Becker, Liam Brierley, Cara Brook, Rebecca Christofferson, Lily Cohen, Tad Dallas, Evan Eskew, Anna Fagre, Maxwell Farrell, Emma Glennon, Sarah Guth, Maxwell Joseph, Nardus Mollentze, Ben Neely, Timothee Poisot, Angela Rasmussen, Sadie Ryan, Anna Siodin, Stephanie Seifert, Erin Sorrell, Colin Carlson

Abstract

Better methods to predict and prevent the emergence of zoonotic viruses could support future efforts to reduce the risk of epidemics. We propose a network science framework for understanding and predicting human and animal susceptibility to viral infections. Related approaches have so far helped to identify basic biological rules that govern cross-species transmission and structure the global virome. We highlight ways to make modelling both accurate and actionable, and discuss the barriers that prevent researchers from translating viral ecology into public health policies that could prevent future pandemics.
Citation
Nature Microbiology
Volume
6

Keywords

modeling, spillover, viral prediction, zoonotic potential

Citation

Albery, G. , Becker, D. , Brierley, L. , Brook, C. , Christofferson, R. , Cohen, L. , Dallas, T. , Eskew, E. , Fagre, A. , Farrell, M. , Glennon, E. , Guth, S. , Joseph, M. , Mollentze, N. , Neely, B. , Poisot, T. , Rasmussen, A. , Ryan, S. , Siodin, A. , Seifert, S. , Sorrell, E. and Carlson, C. (2021), The science of the host–virus network, Nature Microbiology, [online], https://doi.org/10.1038/s41564-021-00999-5 (Accessed December 30, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created November 24, 2021, Updated December 7, 2021