Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Tonnang, Henri EZ, Kangalawe, Richard YM, Yanda, Pius Z
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
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
_version_ 1782181361148231680
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
work_keys_str_mv AT tonnanghenriez predictingandmappingmalariaunderclimatechangescenariosthepotentialredistributionofmalariavectorsinafrica
AT kangalawerichardym predictingandmappingmalariaunderclimatechangescenariosthepotentialredistributionofmalariavectorsinafrica
AT yandapiusz predictingandmappingmalariaunderclimatechangescenariosthepotentialredistributionofmalariavectorsinafrica