The future of zoonotic risk prediction

In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization,...

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Published inPhilosophical transactions of the Royal Society of London. Series B. Biological sciences Vol. 376; no. 1837; p. 20200358
Main Authors Carlson, Colin J., Farrell, Maxwell J., Grange, Zoe, Han, Barbara A., Mollentze, Nardus, Phelan, Alexandra L., Rasmussen, Angela L., Albery, Gregory F., Bett, Bernard, Brett-Major, David M., Cohen, Lily E., Dallas, Tad, Eskew, Evan A., Fagre, Anna C., Forbes, Kristian M., Gibb, Rory, Halabi, Sam, Hammer, Charlotte C., Katz, Rebecca, Kindrachuk, Jason, Muylaert, Renata L., Nutter, Felicia B., Ogola, Joseph, Olival, Kevin J., Rourke, Michelle, Ryan, Sadie J., Ross, Noam, Seifert, Stephanie N., Sironen, Tarja, Standley, Claire J., Taylor, Kishana, Venter, Marietjie, Webala, Paul W.
Format Journal Article
LanguageEnglish
Published The Royal Society 08.11.2021
Subjects
Opinion Piece
Part III: Zoonotic Disease Risk and Impacts
Online AccessGet full text
ISSN0962-8436
1471-2970
1471-2970
DOI10.1098/rstb.2020.0358

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Abstract In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from 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? This article is part of the theme issue ‘Infectious disease macroecology: parasite diversity and dynamics across the globe’.
AbstractList In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from 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? This article is part of the theme issue ‘Infectious disease macroecology: parasite diversity and dynamics across the globe’.
In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from 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? This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from 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? This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.
Author Bett, Bernard
Ogola, Joseph
Olival, Kevin J.
Farrell, Maxwell J.
Rasmussen, Angela L.
Webala, Paul W.
Kindrachuk, Jason
Cohen, Lily E.
Eskew, Evan A.
Katz, Rebecca
Phelan, Alexandra L.
Standley, Claire J.
Fagre, Anna C.
Seifert, Stephanie N.
Gibb, Rory
Taylor, Kishana
Brett-Major, David M.
Forbes, Kristian M.
Muylaert, Renata L.
Ryan, Sadie J.
Mollentze, Nardus
Albery, Gregory F.
Nutter, Felicia B.
Grange, Zoe
Carlson, Colin J.
Sironen, Tarja
Dallas, Tad
Rourke, Michelle
Halabi, Sam
Hammer, Charlotte C.
Venter, Marietjie
Han, Barbara A.
Ross, Noam
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  organization: Center for Global Health Science and Security, Georgetown University Medical Center, Washington, DC 20007, USA
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  givenname: Gregory F.
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  fullname: Albery, Gregory F.
  organization: Department of Biology, Georgetown University, Washington, DC 20007, USA
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  organization: Animal and Human Health Program, International Livestock Research Institute, PO Box 30709-00100, Nairobi, Kenya
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  givenname: David M.
  orcidid: 0000-0002-7583-8495
  surname: Brett-Major
  fullname: Brett-Major, David M.
  organization: Department of Epidemiology, College of Public Health, University of Nebraska Medical Center, Omaha, NE, USA
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  surname: Cohen
  fullname: Cohen, Lily E.
  organization: Icahn School of Medicine at Mount Sinai, New York, NY, USA
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  surname: Dallas
  fullname: Dallas, Tad
  organization: Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70806, USA
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  givenname: Evan A.
  orcidid: 0000-0002-1153-5356
  surname: Eskew
  fullname: Eskew, Evan A.
  organization: Department of Biology, Pacific Lutheran University, Tacoma, WA, USA
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  givenname: Anna C.
  orcidid: 0000-0002-0969-5078
  surname: Fagre
  fullname: Fagre, Anna C.
  organization: Department of Microbiology, Immunology, and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA
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  givenname: Kristian M.
  orcidid: 0000-0002-2112-2707
  surname: Forbes
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  organization: Department of Biological Sciences, University of Arkansas, Fayetteville, AR 72701, USA
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  orcidid: 0000-0002-0965-1649
  surname: Gibb
  fullname: Gibb, Rory
  organization: Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, UK, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
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  givenname: Charlotte C.
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  surname: Hammer
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  organization: Centre for the Study of Existential Risk, University of Cambridge, Cambridge, UK
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  surname: Katz
  fullname: Katz, Rebecca
  organization: Center for Global Health Science and Security, Georgetown University Medical Center, Washington, DC 20007, USA
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  givenname: Jason
  surname: Kindrachuk
  fullname: Kindrachuk, Jason
  organization: Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Manitoba, Canada R3E 0J9
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  givenname: Renata L.
  surname: Muylaert
  fullname: Muylaert, Renata L.
  organization: Molecular Epidemiology and Public Health Laboratory, Hopkirk Research Institute, Massey University, Palmerston North, New Zealand
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  givenname: Felicia B.
  surname: Nutter
  fullname: Nutter, Felicia B.
  organization: Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University, North Grafton, MA 01536, USA, Department of Public Health and Community Medicine, School of Medicine, Tufts University, Boston, MA 02111, USA
– sequence: 23
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  surname: Ogola
  fullname: Ogola, Joseph
  organization: University of Nairobi, Nairobi, Kenya
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  givenname: Kevin J.
  surname: Olival
  fullname: Olival, Kevin J.
  organization: EcoHealth Alliance, New York, NY 10018, USA
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  givenname: Michelle
  surname: Rourke
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  organization: Law Futures Centre, Griffith Law School, Griffith University, Nathan, Queensland 4111, Australia
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  givenname: Sadie J.
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  surname: Ryan
  fullname: Ryan, Sadie J.
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  surname: Ross
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  organization: Department of Virology, University of Helsinki, Helsinki, Finland, Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland
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  givenname: Claire J.
  surname: Standley
  fullname: Standley, Claire J.
  organization: Center for Global Health Science and Security, Georgetown University Medical Center, Washington, DC 20007, USA, Department of Microbiology and Immunology, Georgetown University Medical Center, Washington, DC 20007, USA
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  surname: Taylor
  fullname: Taylor, Kishana
  organization: Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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  organization: Zoonotic Arbo and Respiratory Virus Program, Centre for Viral Zoonoses, Department of Medical Virology, University of Pretoria, Pretoria, South Africa
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  givenname: Paul W.
  surname: Webala
  fullname: Webala, Paul W.
  organization: Department of Forestry and Wildlife Management, Maasai Mara University, Narok 20500, Kenya
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Cites_doi 10.1128/mBio.01730-14
10.1038/s41467-020-17687-3
10.1186/1755-8794-7-S3-S1
10.1073/pnas.2013102117
10.1128/JVI.00601-10
10.3201/eid1112.050997
10.1371/journal.pbio.3000217
10.1371/journal.pntd.0006829
10.3390/v10100519
10.1186/s42826-020-00040-6
10.1016/j.bsheal.2019.10.004
10.1016/S2666-5247(20)30002-1
10.1038/nature05775
10.3201/eid2303.160101
10.1073/pnas.2000429117
10.1126/science.1193550
10.1371/journal.pone.0206926
10.1038/nm.3985
10.1038/nbt.4268
10.1038/s41467-019-11901-7
10.1016/j.virusres.2018.02.013
10.1111/1755-0998.12946
10.1038/nrmicro.2017.45
10.1016/S0140-6736(12)61684-5
10.1098/rstb.2001.0889
10.1371/journal.pone.0196811
10.1002/ece3.6315
10.1016/j.antiviral.2013.07.011
10.3390/v13020252
10.1038/srep14830
10.1016/j.bbrc.2020.03.047
10.1371/journal.pone.0159943
10.1371/journal.pntd.0005135
10.1126/science.1213362
10.1093/ve/vex012
10.1186/s12898-018-0163-2
10.1098/rstb.2019.0296
10.1371/journal.pbio.3000206
10.1038/s41587-020-0518-z
10.1101/2020.04.20.046920
10.1038/s41559-019-0910-6
10.1101/2020.11.02.350439
10.1016/bs.aivir.2017.12.002
10.1016/S0140-6736(15)00946-0
10.1093/cid/ciab456
10.1073/pnas.1606567113
10.1016/S2666-5247(20)30220-2
10.1007/s10096-020-03899-4
10.3389/fmicb.2017.01557
10.1038/s41586-020-2294-9
10.1038/s41564-020-0688-y
10.1086/596510
10.1038/d41586-018-05373-w
10.3390/ijms18061135
10.1128/JVI.02381-16
10.1126/science.aap7463
10.1056/NEJMp1905224
10.1016/j.celrep.2020.01.026
10.1093/bioinformatics/btab147
10.1128/mBio.00598-13
10.1098/rsob.170189
10.1038/s41598-020-69869-0
10.1073/pnas.1521582113
10.1073/pnas.2002324118
10.1073/pnas.1919176117
10.1038/s41591-020-0820-9
10.1016/S0140-6736(17)30003-X
10.1128/JVI.02765-13
10.1098/rstb.2010.0031
10.1038/nature22975
10.7717/peerj.5979
10.7554/eLife.46767
10.1371/journal.pcbi.1005557
10.1101/2020.11.12.379917
10.1101/2021.02.18.431844
10.1016/S0140-6736(20)31873-0
10.2471/BLT.17.199588
10.1038/nrmicro2440
10.1128/mSphere.00262-17
10.1038/nrmicro3405
10.1098/rstb.2016.0166
10.1016/S1473-3099(14)70846-1
10.1098/rspb.2012.2753
10.1073/pnas.1501598112
10.7554/eLife.58989
10.1101/2020.08.07.241729
10.1101/2020.01.24.918755
10.1126/science.288.5472.1789
10.1007/s12250-018-0012-7
10.7554/eLife.18491
10.1101/2020.03.10.986109
10.1038/s41580-020-0259-3
10.1038/s41467-021-21240-1
10.1371/journal.pcbi.1008449
10.1111/nyas.13910
10.1073/pnas.1817323116
10.1038/s41467-017-00923-8
10.1126/science.aap9072
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References e_1_3_6_30_2
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e_1_3_6_38_2
e_1_3_6_11_2
e_1_3_6_34_2
e_1_3_6_15_2
e_1_3_6_57_2
e_1_3_6_99_2
e_1_3_6_105_2
e_1_3_6_65_2
e_1_3_6_42_2
e_1_3_6_84_2
e_1_3_6_101_2
e_1_3_6_61_2
e_1_3_6_80_2
e_1_3_6_2_2
e_1_3_6_6_2
e_1_3_6_27_2
e_1_3_6_23_2
e_1_3_6_69_2
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References_xml – ident: e_1_3_6_86_2
  doi: 10.1128/mBio.01730-14
– ident: e_1_3_6_6_2
  doi: 10.1038/s41467-020-17687-3
– ident: e_1_3_6_61_2
  doi: 10.1186/1755-8794-7-S3-S1
– ident: e_1_3_6_88_2
  doi: 10.1073/pnas.2013102117
– ident: e_1_3_6_56_2
  doi: 10.1128/JVI.00601-10
– ident: e_1_3_6_49_2
  doi: 10.3201/eid1112.050997
– ident: e_1_3_6_77_2
  doi: 10.1371/journal.pbio.3000217
– ident: e_1_3_6_102_2
  doi: 10.1371/journal.pntd.0006829
– ident: e_1_3_6_79_2
  doi: 10.3390/v10100519
– ident: e_1_3_6_89_2
  doi: 10.1186/s42826-020-00040-6
– ident: e_1_3_6_99_2
  doi: 10.1016/j.bsheal.2019.10.004
– ident: e_1_3_6_34_2
  doi: 10.1016/S2666-5247(20)30002-1
– ident: e_1_3_6_22_2
  doi: 10.1038/nature05775
– ident: e_1_3_6_40_2
  doi: 10.3201/eid2303.160101
– ident: e_1_3_6_41_2
  doi: 10.1073/pnas.2000429117
– ident: e_1_3_6_15_2
  doi: 10.1126/science.1193550
– ident: e_1_3_6_11_2
  doi: 10.1371/journal.pone.0206926
– ident: e_1_3_6_85_2
  doi: 10.1038/nm.3985
– ident: e_1_3_6_75_2
  doi: 10.1038/nbt.4268
– ident: e_1_3_6_93_2
  doi: 10.1038/s41467-019-11901-7
– ident: e_1_3_6_80_2
  doi: 10.1016/j.virusres.2018.02.013
– ident: e_1_3_6_96_2
  doi: 10.1111/1755-0998.12946
– ident: e_1_3_6_23_2
  doi: 10.1038/nrmicro.2017.45
– ident: e_1_3_6_19_2
  doi: 10.1016/S0140-6736(12)61684-5
– ident: e_1_3_6_48_2
  doi: 10.1098/rstb.2001.0889
– ident: e_1_3_6_92_2
  doi: 10.1371/journal.pone.0196811
– ident: e_1_3_6_38_2
  doi: 10.1002/ece3.6315
– ident: e_1_3_6_94_2
  doi: 10.1016/j.antiviral.2013.07.011
– ident: e_1_3_6_95_2
  doi: 10.3390/v13020252
– ident: e_1_3_6_50_2
  doi: 10.1038/srep14830
– ident: e_1_3_6_64_2
  doi: 10.1016/j.bbrc.2020.03.047
– ident: e_1_3_6_59_2
  doi: 10.1371/journal.pone.0159943
– ident: e_1_3_6_42_2
  doi: 10.1371/journal.pntd.0005135
– ident: e_1_3_6_83_2
  doi: 10.1126/science.1213362
– ident: e_1_3_6_21_2
  doi: 10.1093/ve/vex012
– ident: e_1_3_6_37_2
  doi: 10.1186/s12898-018-0163-2
– ident: e_1_3_6_2_2
– ident: e_1_3_6_30_2
  doi: 10.1098/rstb.2019.0296
– ident: e_1_3_6_31_2
  doi: 10.1371/journal.pbio.3000206
– ident: e_1_3_6_104_2
  doi: 10.1038/s41587-020-0518-z
– ident: e_1_3_6_106_2
  doi: 10.1101/2020.04.20.046920
– ident: e_1_3_6_4_2
  doi: 10.1038/s41559-019-0910-6
– ident: e_1_3_6_25_2
  doi: 10.1101/2020.11.02.350439
– ident: e_1_3_6_18_2
  doi: 10.1016/bs.aivir.2017.12.002
– ident: e_1_3_6_44_2
  doi: 10.1016/S0140-6736(15)00946-0
– ident: e_1_3_6_69_2
  doi: 10.1093/cid/ciab456
– ident: e_1_3_6_35_2
  doi: 10.1073/pnas.1606567113
– ident: e_1_3_6_98_2
  doi: 10.1016/S2666-5247(20)30220-2
– ident: e_1_3_6_14_2
  doi: 10.1007/s10096-020-03899-4
– ident: e_1_3_6_78_2
  doi: 10.3389/fmicb.2017.01557
– ident: e_1_3_6_105_2
  doi: 10.1038/s41586-020-2294-9
– ident: e_1_3_6_71_2
– ident: e_1_3_6_81_2
  doi: 10.1038/s41564-020-0688-y
– ident: e_1_3_6_54_2
  doi: 10.1086/596510
– ident: e_1_3_6_68_2
  doi: 10.1038/d41586-018-05373-w
– ident: e_1_3_6_62_2
  doi: 10.3390/ijms18061135
– ident: e_1_3_6_60_2
  doi: 10.1128/JVI.02381-16
– ident: e_1_3_6_3_2
  doi: 10.1126/science.aap7463
– ident: e_1_3_6_8_2
  doi: 10.1056/NEJMp1905224
– ident: e_1_3_6_91_2
  doi: 10.1016/j.celrep.2020.01.026
– ident: e_1_3_6_66_2
  doi: 10.1093/bioinformatics/btab147
– volume: 119
  start-page: e300135
  year: 2021
  ident: e_1_3_6_52_2
  article-title: How accurately can we assess zoonotic risk?
  publication-title: PLoS Biol.
– ident: e_1_3_6_73_2
– ident: e_1_3_6_108_2
– ident: e_1_3_6_101_2
  doi: 10.1128/mBio.00598-13
– ident: e_1_3_6_20_2
  doi: 10.1098/rsob.170189
– ident: e_1_3_6_74_2
  doi: 10.1038/s41598-020-69869-0
– ident: e_1_3_6_13_2
  doi: 10.1073/pnas.1521582113
– ident: e_1_3_6_51_2
  doi: 10.1073/pnas.2002324118
– ident: e_1_3_6_55_2
  doi: 10.1073/pnas.1919176117
– ident: e_1_3_6_7_2
– ident: e_1_3_6_87_2
  doi: 10.1038/s41591-020-0820-9
– ident: e_1_3_6_43_2
  doi: 10.1016/S0140-6736(17)30003-X
– ident: e_1_3_6_84_2
  doi: 10.1128/JVI.02765-13
– ident: e_1_3_6_16_2
  doi: 10.1098/rstb.2010.0031
– ident: e_1_3_6_12_2
  doi: 10.1038/nature22975
– ident: e_1_3_6_46_2
  doi: 10.7717/peerj.5979
– ident: e_1_3_6_58_2
  doi: 10.7554/eLife.46767
– ident: e_1_3_6_70_2
  doi: 10.1371/journal.pcbi.1005557
– ident: e_1_3_6_29_2
  doi: 10.1101/2020.11.12.379917
– ident: e_1_3_6_65_2
  doi: 10.1101/2021.02.18.431844
– ident: e_1_3_6_103_2
  doi: 10.1016/S0140-6736(20)31873-0
– ident: e_1_3_6_10_2
  doi: 10.2471/BLT.17.199588
– ident: e_1_3_6_33_2
  doi: 10.1038/nrmicro2440
– ident: e_1_3_6_57_2
  doi: 10.1128/mSphere.00262-17
– ident: e_1_3_6_82_2
  doi: 10.1038/nrmicro3405
– ident: e_1_3_6_97_2
  doi: 10.1098/rstb.2016.0166
– volume: 381
  start-page: 1960
  year: 2013
  ident: e_1_3_6_107_2
  article-title: MERS-CoV: a global challenge
  publication-title: Lancet
– ident: e_1_3_6_45_2
  doi: 10.1016/S1473-3099(14)70846-1
– ident: e_1_3_6_47_2
  doi: 10.1098/rspb.2012.2753
– ident: e_1_3_6_26_2
  doi: 10.1073/pnas.1501598112
– volume: 3
  start-page: e000135
  year: 2017
  ident: e_1_3_6_36_2
  article-title: Patchy promiscuity: machine learning applied to predict the host specificity of Salmonella enterica and Escherichia coli.
  publication-title: Microb. Genome
– ident: e_1_3_6_67_2
– ident: e_1_3_6_76_2
  doi: 10.7554/eLife.58989
– ident: e_1_3_6_72_2
  doi: 10.1101/2020.08.07.241729
– ident: e_1_3_6_28_2
  doi: 10.1101/2020.01.24.918755
– ident: e_1_3_6_17_2
  doi: 10.1126/science.288.5472.1789
– ident: e_1_3_6_100_2
  doi: 10.1007/s12250-018-0012-7
– ident: e_1_3_6_9_2
  doi: 10.7554/eLife.18491
– ident: e_1_3_6_53_2
  doi: 10.1101/2020.03.10.986109
– ident: e_1_3_6_90_2
  doi: 10.1038/s41580-020-0259-3
– ident: e_1_3_6_5_2
  doi: 10.1038/s41467-021-21240-1
– ident: e_1_3_6_63_2
  doi: 10.1371/journal.pcbi.1008449
– ident: e_1_3_6_39_2
  doi: 10.1111/nyas.13910
– ident: e_1_3_6_32_2
  doi: 10.1073/pnas.1817323116
– ident: e_1_3_6_27_2
  doi: 10.1038/s41467-017-00923-8
– ident: e_1_3_6_24_2
  doi: 10.1126/science.aap9072
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Snippet In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will...
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SubjectTerms Opinion Piece
Part III: Zoonotic Disease Risk and Impacts
Title The future of zoonotic risk prediction
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