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Using drivers and transmission pathways to identify SARS-like coronavirus spillover risk hotspots

Author

Listed:
  • Renata L. Muylaert

    (Massey University)

  • David A. Wilkinson

    (UMR ASTRE, CIRAD, INRAE, Université de Montpellier, Plateforme Technologique CYROI, Sainte-Clotilde)

  • Tigga Kingston

    (Texas Tech University)

  • Paolo D’Odorico

    (University of California, Berkeley)

  • Maria Cristina Rulli

    (Politecnico di Milano)

  • Nikolas Galli

    (Politecnico di Milano)

  • Reju Sam John

    (University of Auckland)

  • Phillip Alviola

    (University of the Philippines- Los Banos)

  • David T. S. Hayman

    (Massey University)

Abstract

The emergence of SARS-like coronaviruses is a multi-stage process from wildlife reservoirs to people. Here we characterize multiple drivers—landscape change, host distribution, and human exposure—associated with the risk of spillover of zoonotic SARS-like coronaviruses to help inform surveillance and mitigation activities. We consider direct and indirect transmission pathways by modeling four scenarios with livestock and mammalian wildlife as potential and known reservoirs before examining how access to healthcare varies within clusters and scenarios. We found 19 clusters with differing risk factor contributions within a single country (N = 9) or transboundary (N = 10). High-risk areas were mainly closer (11-20%) rather than far (

Suggested Citation

  • Renata L. Muylaert & David A. Wilkinson & Tigga Kingston & Paolo D’Odorico & Maria Cristina Rulli & Nikolas Galli & Reju Sam John & Phillip Alviola & David T. S. Hayman, 2023. "Using drivers and transmission pathways to identify SARS-like coronavirus spillover risk hotspots," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-42627-2
    DOI: 10.1038/s41467-023-42627-2
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