Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling.

Modelling the spatial distributions of human parasite species is crucial to understanding the environmental determinants of infection as well as for guiding the planning of control programmes. Here, we use ecological niche modelling to map the current potential distribution of the macroparasitic dis...

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Autores principales:	Hannah Slater, Edwin Michael
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/0f95dec9e96243c99718ca0eca1f4aa1
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spelling	oai:doaj.org-article:0f95dec9e96243c99718ca0eca1f4aa12021-11-18T07:27:52ZPredicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling.1932-620310.1371/journal.pone.0032202https://doaj.org/article/0f95dec9e96243c99718ca0eca1f4aa12012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22359670/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Modelling the spatial distributions of human parasite species is crucial to understanding the environmental determinants of infection as well as for guiding the planning of control programmes. Here, we use ecological niche modelling to map the current potential distribution of the macroparasitic disease, lymphatic filariasis (LF), in Africa, and to estimate how future changes in climate and population could affect its spread and burden across the continent. We used 508 community-specific infection presence data collated from the published literature in conjunction with five predictive environmental/climatic and demographic variables, and a maximum entropy niche modelling method to construct the first ecological niche maps describing potential distribution and burden of LF in Africa. We also ran the best-fit model against climate projections made by the HADCM3 and CCCMA models for 2050 under A2a and B2a scenarios to simulate the likely distribution of LF under future climate and population changes. We predict a broad geographic distribution of LF in Africa extending from the west to the east across the middle region of the continent, with high probabilities of occurrence in the Western Africa compared to large areas of medium probability interspersed with smaller areas of high probability in Central and Eastern Africa and in Madagascar. We uncovered complex relationships between predictor ecological niche variables and the probability of LF occurrence. We show for the first time that predicted climate change and population growth will expand both the range and risk of LF infection (and ultimately disease) in an endemic region. We estimate that populations at risk to LF may range from 543 and 804 million currently, and that this could rise to between 1.65 to 1.86 billion in the future depending on the climate scenario used and thresholds applied to signify infection presence.Hannah SlaterEdwin MichaelPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 2, p e32202 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Hannah Slater Edwin Michael Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling.
description	Modelling the spatial distributions of human parasite species is crucial to understanding the environmental determinants of infection as well as for guiding the planning of control programmes. Here, we use ecological niche modelling to map the current potential distribution of the macroparasitic disease, lymphatic filariasis (LF), in Africa, and to estimate how future changes in climate and population could affect its spread and burden across the continent. We used 508 community-specific infection presence data collated from the published literature in conjunction with five predictive environmental/climatic and demographic variables, and a maximum entropy niche modelling method to construct the first ecological niche maps describing potential distribution and burden of LF in Africa. We also ran the best-fit model against climate projections made by the HADCM3 and CCCMA models for 2050 under A2a and B2a scenarios to simulate the likely distribution of LF under future climate and population changes. We predict a broad geographic distribution of LF in Africa extending from the west to the east across the middle region of the continent, with high probabilities of occurrence in the Western Africa compared to large areas of medium probability interspersed with smaller areas of high probability in Central and Eastern Africa and in Madagascar. We uncovered complex relationships between predictor ecological niche variables and the probability of LF occurrence. We show for the first time that predicted climate change and population growth will expand both the range and risk of LF infection (and ultimately disease) in an endemic region. We estimate that populations at risk to LF may range from 543 and 804 million currently, and that this could rise to between 1.65 to 1.86 billion in the future depending on the climate scenario used and thresholds applied to signify infection presence.
format	article
author	Hannah Slater Edwin Michael
author_facet	Hannah Slater Edwin Michael
author_sort	Hannah Slater
title	Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling.
title_short	Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling.
title_full	Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling.
title_fullStr	Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling.
title_full_unstemmed	Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling.
title_sort	predicting the current and future potential distributions of lymphatic filariasis in africa using maximum entropy ecological niche modelling.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/0f95dec9e96243c99718ca0eca1f4aa1
work_keys_str_mv	AT hannahslater predictingthecurrentandfuturepotentialdistributionsoflymphaticfilariasisinafricausingmaximumentropyecologicalnichemodelling AT edwinmichael predictingthecurrentandfuturepotentialdistributionsoflymphaticfilariasisinafricausingmaximumentropyecologicalnichemodelling
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Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling.

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