Updates to the zoonotic niche map of Ebola virus disease in Africa

As the outbreak of Ebola virus disease (EVD) in West Africa is now contained, attention is turning from control to future outbreak prediction and prevention. Building on a previously published zoonotic niche map (Pigott et al., 2014), this study incorporates new human and animal occurrence data and...

Full description

Bibliographic Details
Main Authors:	David M Pigott, Anoushka I Millear, Lucas Earl, Chloe Morozoff, Barbara A Han, Freya M Shearer, Daniel J Weiss, Oliver J Brady, Moritz UG Kraemer, Catherine L Moyes, Samir Bhatt, Peter W Gething, Nick Golding, Simon I Hay
Format:	Article
Language:	English
Published:	eLife Sciences Publications Ltd 2016-07-01
Series:	eLife
Subjects:	boosted regression tree disease mapping ebola Ebola virus niche based modelling species distribution modelling
Online Access:	https://elifesciences.org/articles/16412

id	doaj-a216443e2f084c6c8c52a684fa6b203a
record_format	Article
spelling	doaj-a216443e2f084c6c8c52a684fa6b203a2021-05-05T00:28:49ZengeLife Sciences Publications LtdeLife2050-084X2016-07-01510.7554/eLife.16412Updates to the zoonotic niche map of Ebola virus disease in AfricaDavid M Pigott0Anoushka I Millear1Lucas Earl2Chloe Morozoff3https://orcid.org/0000-0002-3254-5553Barbara A Han4Freya M Shearer5Daniel J Weiss6Oliver J Brady7Moritz UG Kraemer8https://orcid.org/0000-0001-8838-7147Catherine L Moyes9https://orcid.org/0000-0002-8028-4079Samir Bhatt10Peter W Gething11Nick Golding12Simon I Hay13https://orcid.org/0000-0002-0611-7272Institute for Health Metrics and Evaluation, University of Washington, Seattle, United States; Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United KingdomInstitute for Health Metrics and Evaluation, University of Washington, Seattle, United StatesInstitute for Health Metrics and Evaluation, University of Washington, Seattle, United StatesInstitute for Health Metrics and Evaluation, University of Washington, Seattle, United StatesCary Institute of Ecosystem Studies, New York, United StatesOxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United KingdomSpatial Ecology and Epidemiology Group, University of Oxford, Oxford, United Kingdom; Department of Zoology, University of Oxford, Oxford, United KingdomOxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United KingdomSpatial Ecology and Epidemiology Group, University of Oxford, Oxford, United Kingdom; Department of Zoology, University of Oxford, Oxford, United KingdomOxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United KingdomSpatial Ecology and Epidemiology Group, University of Oxford, Oxford, United Kingdom; Department of Zoology, University of Oxford, Oxford, United KingdomSpatial Ecology and Epidemiology Group, University of Oxford, Oxford, United Kingdom; Department of Zoology, University of Oxford, Oxford, United KingdomOxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom; Department of BioSciences, University of Melbourne, Parkville, AustraliaInstitute for Health Metrics and Evaluation, University of Washington, Seattle, United States; Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United KingdomAs the outbreak of Ebola virus disease (EVD) in West Africa is now contained, attention is turning from control to future outbreak prediction and prevention. Building on a previously published zoonotic niche map (Pigott et al., 2014), this study incorporates new human and animal occurrence data and expands upon the way in which potential bat EVD reservoir species are incorporated. This update demonstrates the potential for incorporating and updating data used to generate the predicted suitability map. A new data portal for sharing such maps is discussed. This output represents the most up-to-date estimate of the extent of EVD zoonotic risk in Africa. These maps can assist in strengthening surveillance and response capacity to contain viral haemorrhagic fevers.https://elifesciences.org/articles/16412boosted regression treedisease mappingebolaEbola virusniche based modellingspecies distribution modelling
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	David M Pigott Anoushka I Millear Lucas Earl Chloe Morozoff Barbara A Han Freya M Shearer Daniel J Weiss Oliver J Brady Moritz UG Kraemer Catherine L Moyes Samir Bhatt Peter W Gething Nick Golding Simon I Hay
spellingShingle	David M Pigott Anoushka I Millear Lucas Earl Chloe Morozoff Barbara A Han Freya M Shearer Daniel J Weiss Oliver J Brady Moritz UG Kraemer Catherine L Moyes Samir Bhatt Peter W Gething Nick Golding Simon I Hay Updates to the zoonotic niche map of Ebola virus disease in Africa eLife boosted regression tree disease mapping ebola Ebola virus niche based modelling species distribution modelling
author_facet	David M Pigott Anoushka I Millear Lucas Earl Chloe Morozoff Barbara A Han Freya M Shearer Daniel J Weiss Oliver J Brady Moritz UG Kraemer Catherine L Moyes Samir Bhatt Peter W Gething Nick Golding Simon I Hay
author_sort	David M Pigott
title	Updates to the zoonotic niche map of Ebola virus disease in Africa
title_short	Updates to the zoonotic niche map of Ebola virus disease in Africa
title_full	Updates to the zoonotic niche map of Ebola virus disease in Africa
title_fullStr	Updates to the zoonotic niche map of Ebola virus disease in Africa
title_full_unstemmed	Updates to the zoonotic niche map of Ebola virus disease in Africa
title_sort	updates to the zoonotic niche map of ebola virus disease in africa
publisher	eLife Sciences Publications Ltd
series	eLife
issn	2050-084X
publishDate	2016-07-01
description	As the outbreak of Ebola virus disease (EVD) in West Africa is now contained, attention is turning from control to future outbreak prediction and prevention. Building on a previously published zoonotic niche map (Pigott et al., 2014), this study incorporates new human and animal occurrence data and expands upon the way in which potential bat EVD reservoir species are incorporated. This update demonstrates the potential for incorporating and updating data used to generate the predicted suitability map. A new data portal for sharing such maps is discussed. This output represents the most up-to-date estimate of the extent of EVD zoonotic risk in Africa. These maps can assist in strengthening surveillance and response capacity to contain viral haemorrhagic fevers.
topic	boosted regression tree disease mapping ebola Ebola virus niche based modelling species distribution modelling
url	https://elifesciences.org/articles/16412
work_keys_str_mv	AT davidmpigott updatestothezoonoticnichemapofebolavirusdiseaseinafrica AT anoushkaimillear updatestothezoonoticnichemapofebolavirusdiseaseinafrica AT lucasearl updatestothezoonoticnichemapofebolavirusdiseaseinafrica AT chloemorozoff updatestothezoonoticnichemapofebolavirusdiseaseinafrica AT barbaraahan updatestothezoonoticnichemapofebolavirusdiseaseinafrica AT freyamshearer updatestothezoonoticnichemapofebolavirusdiseaseinafrica AT danieljweiss updatestothezoonoticnichemapofebolavirusdiseaseinafrica AT oliverjbrady updatestothezoonoticnichemapofebolavirusdiseaseinafrica AT moritzugkraemer updatestothezoonoticnichemapofebolavirusdiseaseinafrica AT catherinelmoyes updatestothezoonoticnichemapofebolavirusdiseaseinafrica AT samirbhatt updatestothezoonoticnichemapofebolavirusdiseaseinafrica AT peterwgething updatestothezoonoticnichemapofebolavirusdiseaseinafrica AT nickgolding updatestothezoonoticnichemapofebolavirusdiseaseinafrica AT simonihay updatestothezoonoticnichemapofebolavirusdiseaseinafrica
_version_	1721476286104207360

Updates to the zoonotic niche map of Ebola virus disease in Africa

Similar Items