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

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dc.citation.volume14
dc.contributor.authorMuylaert R
dc.contributor.authorWilkinson D
dc.contributor.authorKingston T
dc.contributor.authorD’Odorico P
dc.contributor.authorRulli MC
dc.contributor.authorGalli N
dc.contributor.authorJohn RS
dc.contributor.authorAlviola P
dc.contributor.authorHayman DTS
dc.date.accessioned2024-08-07T20:53:56Z
dc.date.available2024-08-07T20:53:56Z
dc.date.issued2023-05-30
dc.description.abstractThe 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 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 (<1%) from healthcare. Areas far from healthcare reveal healthcare access inequalities, especially Scenario 3, which includes wild mammals as secondary hosts. China (N=2) and Indonesia (N=1) had clusters with the highest risk. Our findings can help stakeholders in land use planning integrating healthcare implementation and One Health actions.
dc.description.confidentialfalse
dc.edition.edition2023
dc.identifier.citationMuylaert R, Wilkinson D, Kingston T, D’Odorico P, Rulli MC, Galli N, John RS, Alviola P, Hayman D. (2022). Using drivers and transmission pathways to identify SARS-like coronavirus spillover risk hotspots. Nature Communications. 14.
dc.identifier.doi10.1101/2022.12.08.518776
dc.identifier.eissn2041-1723
dc.identifier.elements-typejournal-article
dc.identifier.number6854
dc.identifier.urihttps://mro.massey.ac.nz/handle/10179/71227
dc.languageEnglish
dc.publisherSpringer Nature Limited.
dc.publisher.urihttps://www.nature.com/articles/s41467-023-42627-2
dc.relation.isPartOfNature Communications
dc.rights© The Author(s) 2023
dc.rightsCC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleUsing drivers and transmission pathways to identify SARS-like coronavirus spillover risk hotspots
dc.typeother
pubs.elements-id460558
pubs.organisational-groupOther
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