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Nat Commun. 2017 Oct 24;8(1):1124. doi: 10.1038/s41467-017-00923-8.

Global hotspots and correlates of emerging zoonotic diseases.

Author information

1
EcoHealth Alliance, 460 West 34th Street, 17th Floor, New York, NY, 10001, USA.
2
Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK.
3
Grantham Institute - Climate Change and the Environment, Imperial College London, Exhibition Road, London, SW7 2AZ, UK.
4
Mailman School of Public Health, Columbia University, 722 West 168th St #1504, New York, NY, 10032, USA.
5
Global Mammal Assessment Program, Department of Biology and Biotechnologies, Sapienza University of Rome, Viale dell'Università 32, 00185, Rome, Italy.
6
ARC Centre of Excellence for Environmental Decisions, Centre for Biosiversity and Conservation Science, University of Queensland, St Lucia, QLD, 4072, Australia.
7
School of Earth and Environmental Sciences, The University of Queensland, St Lucia, QLD, 4072, Australia.
8
EcoHealth Alliance, 460 West 34th Street, 17th Floor, New York, NY, 10001, USA. daszak@ecohealthalliance.org.

Abstract

Zoonoses originating from wildlife represent a significant threat to global health, security and economic growth, and combatting their emergence is a public health priority. However, our understanding of the mechanisms underlying their emergence remains rudimentary. Here we update a global database of emerging infectious disease (EID) events, create a novel measure of reporting effort, and fit boosted regression tree models to analyze the demographic, environmental and biological correlates of their occurrence. After accounting for reporting effort, we show that zoonotic EID risk is elevated in forested tropical regions experiencing land-use changes and where wildlife biodiversity (mammal species richness) is high. We present a new global hotspot map of spatial variation in our zoonotic EID risk index, and partial dependence plots illustrating relationships between events and predictors. Our results may help to improve surveillance and long-term EID monitoring programs, and design field experiments to test underlying mechanisms of zoonotic disease emergence.

PMID:
29066781
PMCID:
PMC5654761
DOI:
10.1038/s41467-017-00923-8
[Indexed for MEDLINE]
Free PMC Article

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