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dc.contributor.authorRedding, David W.
dc.contributor.authorMoses, Lina M.
dc.contributor.authorCunningham, Andrew A.
dc.contributor.authorWood, James
dc.contributor.authorJones, Kate E.
dc.date.accessioned2016-05-19T08:49:28Z
dc.date.available2016-05-19T08:49:28Z
dc.date.issued2016-06-13
dc.identifier.citationRedding et al. Methods in Ecology and Evolution (2016) 7: 646-655.en
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/256060
dc.descriptionThis is the final version of the article. It first appeared from Wiley via https://doi.org/10.1111/2041-210X.12549.en
dc.description.abstract1. Human infectious diseases are a significant threat to global human health and economies (e.g., Ebola, SARs), with the majority of infectious diseases having an animal source (zoonotic). Despite their importance, the lack of a quantitative predictive framework hampers our understanding of how spill-overs of zoonotic infectious diseases into the human population will be impacted by global environmental stressors. 2. Here, we create an environmental-mechanistic model for understanding the impact of global change on the probability of zoonotic disease reservoir host-human spill-over events. As a case study, we focus on Lassa fever virus (LAS). We firstly quantify the spatial determinants of LAS outbreaks, including the phylogeographic distribution of its reservoir host Natal multimammate rat (Mastomys natalensis) (LAS host). Secondly, we use these determinants to inform our environmental-mechanistic model to estimate present day LAS spill-over events and the predicted impact of climate change, human population growth, and land use by 2070. 3. We find phylogeographic evidence to suggest that LAS is confined to only one clade of LAS host (Western clade Mastomys natalensis), and that the probability of its occurrence was a major determinant of the spatial variation in LAS historical outbreaks (69.8%), along with human population density (20.4%). Our estimates for present day LAS spill- over events from our environmental-mechanistic model were consistent with observed patterns, and we predict an increase in events per year by 2070 from 195,125 to 406,725 within the LAS endemic western African region. Of the component drivers, climate change and human population growth are predicted to have the largest effects by increasing landscape suitability for the host and human-host contact rates, while land use change has only a weak impact on the number of future events. 4. LAS spill-over events did not respond uniformly to global environmental stressors, and we suggest that understanding the impact of global change on zoonotic infectious disease emergence requires an understanding of how reservoir host species respond to environmental change. Our environmental-mechanistic modelling methodology provides a novel generalizable framework to understand the impact of global change on the spill- over of zoonotic diseases.en
dc.description.sponsorshipWe thank P. Sivasubramaniam and R. Gibb for technical assistance, and C. Watts, C. Carbone, T. Lucas, and R. Freeman for comments on previous versions of the manuscript. This work, Dynamic Drivers of Disease in Africa Consortium, NERC project no. NE- J001570-1 was funded with support from the Ecosystem Services for Poverty Alleviation Programme (ESPA). The ESPA programme is funded by the Department for International Development (DFID), the Economic and Social Research Council (ESRC) and the Natural Environment Research Council (NERC). AAC is additionally supported by a Royal Society Wolfson Research Merit Award.en
dc.language.isoenen
dc.publisherWileyen
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectinfectious diseaseen
dc.subjectspill-over eventsen
dc.subjectMastomys natalensisen
dc.subjectland-use changeen
dc.subjectWest Africaen
dc.subjecthaemorrhagic diseaseen
dc.subjectclimate changeen
dc.titleEnvironmental-mechanistic modelling of the impact of global change on human zoonotic 2 disease emergence: A case study of Lassa feveren
dc.title.alternativeMacro-mechanistic modelling of zoonotic disease emergenceen
dc.typeArticleen
dc.type.versionpublishedversionen
prism.edition5th anniversary
prism.endingPage655
prism.endingPage655
prism.publicationDate2016
prism.publicationNameMethods in Ecology and Evolution
prism.startingPage646
prism.volume7
dc.rioxxterms.funderNERC
dc.rioxxterms.funderESRC
dc.rioxxterms.projectidNE- J001570-1
rioxxterms.versionofrecord10.1111/2041-210X.12549
rioxxterms.versionVoR
rioxxterms.freetoread.startdate2100-01-01


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International