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      Reconstructing the emergence of a lethal infectious disease of wildlife supports a key role for spread through translocations by humans

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          Abstract

          There have been few reconstructions of wildlife disease emergences, despite their extensive impact on biodiversity and human health. This is in large part attributable to the lack of structured and robust spatio-temporal datasets. We overcame logistical problems of obtaining suitable information by using data from a citizen science project and formulating spatio-temporal models of the spread of a wildlife pathogen (genus Ranavirus, infecting amphibians). We evaluated three main hypotheses for the rapid increase in disease reports in the UK: that outbreaks were being reported more frequently, that climate change had altered the interaction between hosts and a previously widespread pathogen, and that disease was emerging due to spatial spread of a novel pathogen. Our analysis characterized localized spread from nearby ponds, consistent with amphibian dispersal, but also revealed a highly significant trend for elevated rates of additional outbreaks in localities with higher human population density—pointing to human activities in also spreading the virus. Phylogenetic analyses of pathogen genomes support the inference of at least two independent introductions into the UK. Together these results point strongly to humans repeatedly translocating ranaviruses into the UK from other countries and between UK ponds, and therefore suggest potential control measures.

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          Most cited references56

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          Global trends in emerging infectious diseases

          The next new disease Emerging infectious diseases are a major threat to health: AIDS, SARS, drug-resistant bacteria and Ebola virus are among the more recent examples. By identifying emerging disease 'hotspots', the thinking goes, it should be possible to spot health risks at an early stage and prepare containment strategies. An analysis of over 300 examples of disease emerging between 1940 and 2004 suggests that these hotspots can be accurately mapped based on socio-economic, environmental and ecological factors. The data show that the surveillance effort, and much current research spending, is concentrated in developed economies, yet the risk maps point to developing countries as the more likely source of new diseases. Supplementary information The online version of this article (doi:10.1038/nature06536) contains supplementary material, which is available to authorized users.
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            Emerging Infectious Diseases of Wildlife-- Threats to Biodiversity and Human Health

            P. Daszak (2000)
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              Emerging infectious diseases of wildlife--threats to biodiversity and human health.

              Emerging infectious diseases (EIDs) of free-living wild animals can be classified into three major groups on the basis of key epizootiological criteria: (i) EIDs associated with "spill-over" from domestic animals to wildlife populations living in proximity; (ii) EIDs related directly to human intervention, via host or parasite translocations; and (iii) EIDs with no overt human or domestic animal involvement. These phenomena have two major biological implications: first, many wildlife species are reservoirs of pathogens that threaten domestic animal and human health; second, wildlife EIDs pose a substantial threat to the conservation of global biodiversity.
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                Author and article information

                Journal
                Proc Biol Sci
                Proc. Biol. Sci
                RSPB
                royprsb
                Proceedings of the Royal Society B: Biological Sciences
                The Royal Society
                0962-8452
                1471-2954
                28 September 2016
                28 September 2016
                : 283
                : 1839
                : 20160952
                Affiliations
                [1 ]UCL Genetics Institute, University College London , Darwin Building, Gower Street, London WC1E 6BT, UK
                [2 ]Institute of Zoology, Zoological Society of London , London NW1 4RY, UK
                [3 ]School of Biological and Chemical Sciences, Queen Mary University of London , Mile End Road, London E1 4NS, UK
                [4 ]Herpetofauna Consultants International , Triton House, Bramfield, Halesworth, Suffolk IP19 9AE, UK
                Author notes

                Electronic supplementary material is available online at https://dx.doi.org/10.6084/m9.figshare.c.3469740.

                Author information
                http://orcid.org/0000-0001-6983-6250
                http://orcid.org/0000-0002-0336-9706
                http://orcid.org/0000-0002-4801-9312
                Article
                rspb20160952
                10.1098/rspb.2016.0952
                5046891
                27683363
                689af992-36f6-41f0-bfb9-cbf50aac5dc1
                © 2016 The Authors.

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : 29 April 2016
                : 31 August 2016
                Funding
                Funded by: Systematics and Taxonomy Research Scheme (SynTax);
                Funded by: European Research Council, http://dx.doi.org/10.13039/501100000781;
                Award ID: 260801-BIG-IDEA
                Funded by: Natural Environment Research Council, http://dx.doi.org/10.13039/501100000270;
                Award ID: NE/G011885/1
                Award ID: NE/M000338/1
                Award ID: NE/M000591/1
                Award ID: NE/M00080X/1
                Categories
                1001
                60
                87
                Research Articles
                Custom metadata
                September 28, 2016

                Life sciences
                pathogen pollution,ranavirus,citizen science,wildlife disease,anthropogenic drivers,spatio-temporal models

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