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

Muylaert Renata L., Wilkinson David, Kingston Tigga, D'Odorico Paolo, Rulli Maria Cristina, Galli Nikolas, John Reju Sam, Alviola Phillip, Hayman David T.S.. 2023. Using drivers and transmission pathways to identify SARS-like coronavirus spillover risk hotspots. Nature Communications, 14:6854, 11 p.

https://doi.org/10.1038/s41467-023-42627-2

Article de revue ; Article de recherche ; Article de revue à facteur d'impact

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Url - autres données associées : https://github.com/renatamuy/hotspots/ / Url - jeu de données - Entrepôt autre : https://zenodo.org/records/10120206

Résumé : 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 ( < 1%) from healthcare. Areas far from healthcare reveal healthcare access inequalities, especially Scenario 3, which includes wild mammals and not livestock 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.

Mots-clés Agrovoc : transmission des maladies, facteur de risque, bétail, surveillance épidémiologique, utilisation des terres, Chiroptera, déboisement, évaluation du risque, télédétection, épidémiologie, aménagement du territoire, paysage