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      Global hotspots and correlates of emerging zoonotic diseases

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          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.

          Abstract

          The risk of epidemics originating from wild animals demands close monitoring of emerging infectious disease (EID) events and their predictors. Here, the authors update a global database of EID events, analyze their environmental and biological correlates, and present a new global hotspot map of zoonotic EID risk.

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          Most cited references31

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          Selecting pseudo-absences for species distribution models: how, where and how many?

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            Factors in the emergence of infectious diseases.

            "Emerging" infectious diseases can be defined as infections that have newly appeared in a population or have existed but are rapidly increasing in incidence or geographic range. Among recent examples are HIV/AIDS, hantavirus pulmonary syndrome, Lyme disease, and hemolytic uremic syndrome (a foodborne infection caused by certain strains of Escherichia coli). Specific factors precipitating disease emergence can be identified in virtually all cases. These include ecological, environmental, or demographic factors that place people at increased contact with a previously unfamiliar microbe or its natural host or promote dissemination. These factors are increasing in prevalence; this increase, together with the ongoing evolution of viral and microbial variants and selection for drug resistance, suggests that infections will continue to emerge and probably increase and emphasizes the urgent need for effective surveillance and control. Dr. David Satcher's article and this overview inaugurate Perspectives, a regular section in this journal intended to present and develop unifying concepts and strategies for considering emerging infections and their underlying factors. The editors welcome, as contributions to the Perspectives section, overviews, syntheses, and case studies that shed light on how and why infections emerge, and how they may be anticipated and prevented.
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              How should pathogen transmission be modelled?

              Host-pathogen models are essential for designing strategies for managing disease threats to humans, wild animals and domestic animals. The behaviour of these models is greatly affected by the way in which transmission between infected and susceptible hosts is modelled. Since host-pathogen models were first developed at the beginning of the 20th century, the 'mass action' assumption has almost always been used for transmission. Recently, however, it has been suggested that mass action has often been modelled wrongly. Alternative models of transmission are beginning to appear, as are empirical tests of transmission dynamics.
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                Author and article information

                Contributors
                daszak@ecohealthalliance.org
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                24 October 2017
                24 October 2017
                2017
                : 8
                : 1124
                Affiliations
                [1 ]ISNI 0000 0004 0409 4702, GRID grid.420826.a, EcoHealth Alliance, ; 460 West 34th Street, 17th Floor, New York, NY 10001 USA
                [2 ]ISNI 0000 0001 2113 8111, GRID grid.7445.2, Department of Infectious Disease Epidemiology, School of Public Health, , Imperial College London, ; St Mary’s Campus, Norfolk Place, London, W2 1PG UK
                [3 ]ISNI 0000 0001 2113 8111, GRID grid.7445.2, Grantham Institute – Climate Change and the Environment, , Imperial College London, ; Exhibition Road, London, SW7 2AZ UK
                [4 ]ISNI 0000000419368729, GRID grid.21729.3f, Mailman School of Public Health, , Columbia University, ; 722 West 168th St #1504, New York, NY 10032 USA
                [5 ]GRID grid.7841.a, Global Mammal Assessment Program, Department of Biology and Biotechnologies, , Sapienza University of Rome, ; Viale dell’Università 32, 00185 Rome, Italy
                [6 ]ISNI 0000 0000 9320 7537, GRID grid.1003.2, ARC Centre of Excellence for Environmental Decisions, Centre for Biosiversity and Conservation Science, , University of Queensland, ; St Lucia, QLD 4072 Australia
                [7 ]ISNI 0000 0000 9320 7537, GRID grid.1003.2, School of Earth and Environmental Sciences, , The University of Queensland, ; St Lucia, QLD 4072 Australia
                Author information
                http://orcid.org/0000-0002-5614-7496
                Article
                923
                10.1038/s41467-017-00923-8
                5654761
                29066781
                c5864d05-288d-426b-aec7-42113bdba986
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 1 June 2016
                : 7 August 2017
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