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Predicting and mapping malaria under climate change scenarios: the potential redistribution of malaria vectors in Africa
BACKGROUND: Malaria is rampant in Africa and causes untold mortality and morbidity. Vector-borne diseases are climate sensitive and this has raised considerable concern over the implications of climate change on future disease risk. The problem of malaria vectors (Anopheles mosquitoes) shifting from...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2873524/ https://www.ncbi.nlm.nih.gov/pubmed/20416059 http://dx.doi.org/10.1186/1475-2875-9-111 |
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author | Tonnang, Henri EZ Kangalawe, Richard YM Yanda, Pius Z |
author_facet | Tonnang, Henri EZ Kangalawe, Richard YM Yanda, Pius Z |
author_sort | Tonnang, Henri EZ |
collection | PubMed |
description | BACKGROUND: Malaria is rampant in Africa and causes untold mortality and morbidity. Vector-borne diseases are climate sensitive and this has raised considerable concern over the implications of climate change on future disease risk. The problem of malaria vectors (Anopheles mosquitoes) shifting from their traditional locations to invade new zones is an important concern. The vision of this study was to exploit the sets of information previously generated by entomologists, e.g. on geographical range of vectors and malaria distribution, to build models that will enable prediction and mapping the potential redistribution of Anopheles mosquitoes in Africa. METHODS: The development of the modelling tool was carried out through calibration of CLIMEX parameters. The model helped estimate the potential geographical distribution and seasonal abundance of the species in relation to climatic factors. These included temperature, rainfall and relative humidity, which characterized the living environment for Anopheles mosquitoes. The same parameters were used in determining the ecoclimatic index (EI). The EI values were exported to a GIS package for special analysis and proper mapping of the potential future distribution of Anopheles gambiae and Anophles arabiensis within the African continent under three climate change scenarios. RESULTS: These results have shown that shifts in these species boundaries southward and eastward of Africa may occur rather than jumps into quite different climatic environments. In the absence of adequate control, these predictions are crucial in understanding the possible future geographical range of the vectors and the disease, which could facilitate planning for various adaptation options. CONCLUSION: Thus, the outputs from this study will be helpful at various levels of decision making, for example, in setting up of an early warning and sustainable strategies for climate change and climate change adaptation for malaria vectors control programmes in Africa. |
format | Text |
id | pubmed-2873524 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-28735242010-05-20 Predicting and mapping malaria under climate change scenarios: the potential redistribution of malaria vectors in Africa Tonnang, Henri EZ Kangalawe, Richard YM Yanda, Pius Z Malar J Review BACKGROUND: Malaria is rampant in Africa and causes untold mortality and morbidity. Vector-borne diseases are climate sensitive and this has raised considerable concern over the implications of climate change on future disease risk. The problem of malaria vectors (Anopheles mosquitoes) shifting from their traditional locations to invade new zones is an important concern. The vision of this study was to exploit the sets of information previously generated by entomologists, e.g. on geographical range of vectors and malaria distribution, to build models that will enable prediction and mapping the potential redistribution of Anopheles mosquitoes in Africa. METHODS: The development of the modelling tool was carried out through calibration of CLIMEX parameters. The model helped estimate the potential geographical distribution and seasonal abundance of the species in relation to climatic factors. These included temperature, rainfall and relative humidity, which characterized the living environment for Anopheles mosquitoes. The same parameters were used in determining the ecoclimatic index (EI). The EI values were exported to a GIS package for special analysis and proper mapping of the potential future distribution of Anopheles gambiae and Anophles arabiensis within the African continent under three climate change scenarios. RESULTS: These results have shown that shifts in these species boundaries southward and eastward of Africa may occur rather than jumps into quite different climatic environments. In the absence of adequate control, these predictions are crucial in understanding the possible future geographical range of the vectors and the disease, which could facilitate planning for various adaptation options. CONCLUSION: Thus, the outputs from this study will be helpful at various levels of decision making, for example, in setting up of an early warning and sustainable strategies for climate change and climate change adaptation for malaria vectors control programmes in Africa. BioMed Central 2010-04-23 /pmc/articles/PMC2873524/ /pubmed/20416059 http://dx.doi.org/10.1186/1475-2875-9-111 Text en Copyright ©2010 Tonnang et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Tonnang, Henri EZ Kangalawe, Richard YM Yanda, Pius Z Predicting and mapping malaria under climate change scenarios: the potential redistribution of malaria vectors in Africa |
title | Predicting and mapping malaria under climate change scenarios: the potential redistribution of malaria vectors in Africa |
title_full | Predicting and mapping malaria under climate change scenarios: the potential redistribution of malaria vectors in Africa |
title_fullStr | Predicting and mapping malaria under climate change scenarios: the potential redistribution of malaria vectors in Africa |
title_full_unstemmed | Predicting and mapping malaria under climate change scenarios: the potential redistribution of malaria vectors in Africa |
title_short | Predicting and mapping malaria under climate change scenarios: the potential redistribution of malaria vectors in Africa |
title_sort | predicting and mapping malaria under climate change scenarios: the potential redistribution of malaria vectors in africa |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2873524/ https://www.ncbi.nlm.nih.gov/pubmed/20416059 http://dx.doi.org/10.1186/1475-2875-9-111 |
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