Malaria around large dams in Africa: effect of environmental and transmission endemicity factors

Background: The impact of large dams on malaria has received widespread attention. However, understanding how dam topography and transmission endemicity influence malaria incidences is limited. Methods: Data from the European Commission’s Joint Research Center and Shuttle Radar Topography Mission we...

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Autores principales: Kibret, S., Lautze, Jonathan F., McCartney, Matthew P., Nhamo, Luxon, Yan, G.
Formato: Journal Article
Lenguaje:Inglés
Publicado: Springer 2019
Materias:
Acceso en línea:https://hdl.handle.net/10568/105726
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author Kibret, S.
Lautze, Jonathan F.
McCartney, Matthew P.
Nhamo, Luxon
Yan, G.
author_browse Kibret, S.
Lautze, Jonathan F.
McCartney, Matthew P.
Nhamo, Luxon
Yan, G.
author_facet Kibret, S.
Lautze, Jonathan F.
McCartney, Matthew P.
Nhamo, Luxon
Yan, G.
author_sort Kibret, S.
collection Repository of Agricultural Research Outputs (CGSpace)
description Background: The impact of large dams on malaria has received widespread attention. However, understanding how dam topography and transmission endemicity influence malaria incidences is limited. Methods: Data from the European Commission’s Joint Research Center and Shuttle Radar Topography Mission were used to determine reservoir perimeters and shoreline slope of African dams. Georeferenced data from the Malaria Atlas Project (MAP) were used to estimate malaria incidence rates in communities near reservoir shorelines. Population data from the WorldPop database were used to estimate the population at risk of malaria around dams in stable and unstable areas. Results: The data showed that people living near (< 5 km) large dams in sub-Saharan Africa grew from 14.4 million in 2000 to 18.7 million in 2015. Overall, across sub-Saharan Africa between 0.7 and 1.6 million malaria cases per year are attributable to large dams. Whilst annual malaria incidence declined markedly in both stable and unstable areas between 2000 and 2015, the malaria impact of dams appeared to increase in unstable areas, but decreased in stable areas. Shoreline slope was found to be the most important malaria risk factor in dam-affected geographies, explaining 41–82% (P < 0.001) of the variation in malaria incidence around reservoirs. Conclusion: Gentler, more gradual shoreline slopes were associated with much greater malaria risk. Dam-related environmental variables such as dam topography and shoreline slopes are an important factor that should be considered in efforts to predict and control malaria around dams.
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spelling CGSpace1057262025-03-11T09:50:20Z Malaria around large dams in Africa: effect of environmental and transmission endemicity factors Kibret, S. Lautze, Jonathan F. McCartney, Matthew P. Nhamo, Luxon Yan, G. malaria vector-borne diseases dams environmental effects disease transmission endemics mosquitoes anopheles breeding habitats water reservoirs slope topography climatic data communities health hazards Background: The impact of large dams on malaria has received widespread attention. However, understanding how dam topography and transmission endemicity influence malaria incidences is limited. Methods: Data from the European Commission’s Joint Research Center and Shuttle Radar Topography Mission were used to determine reservoir perimeters and shoreline slope of African dams. Georeferenced data from the Malaria Atlas Project (MAP) were used to estimate malaria incidence rates in communities near reservoir shorelines. Population data from the WorldPop database were used to estimate the population at risk of malaria around dams in stable and unstable areas. Results: The data showed that people living near (< 5 km) large dams in sub-Saharan Africa grew from 14.4 million in 2000 to 18.7 million in 2015. Overall, across sub-Saharan Africa between 0.7 and 1.6 million malaria cases per year are attributable to large dams. Whilst annual malaria incidence declined markedly in both stable and unstable areas between 2000 and 2015, the malaria impact of dams appeared to increase in unstable areas, but decreased in stable areas. Shoreline slope was found to be the most important malaria risk factor in dam-affected geographies, explaining 41–82% (P < 0.001) of the variation in malaria incidence around reservoirs. Conclusion: Gentler, more gradual shoreline slopes were associated with much greater malaria risk. Dam-related environmental variables such as dam topography and shoreline slopes are an important factor that should be considered in efforts to predict and control malaria around dams. 2019-12 2019-11-14T03:29:47Z 2019-11-14T03:29:47Z Journal Article https://hdl.handle.net/10568/105726 en Open Access Springer Kibret, S.; Lautze, Jonathan; McCartney, Matthew; Nhamo, Luxon; Yan, G. 2019. Malaria around large dams in Africa: effect of environmental and transmission endemicity factors. Malaria Journal, 18:1-12. doi: 10.1186/s12936-019-2933-5
spellingShingle malaria
vector-borne diseases
dams
environmental effects
disease transmission
endemics
mosquitoes
anopheles
breeding habitats
water reservoirs
slope
topography
climatic data
communities
health hazards
Kibret, S.
Lautze, Jonathan F.
McCartney, Matthew P.
Nhamo, Luxon
Yan, G.
Malaria around large dams in Africa: effect of environmental and transmission endemicity factors
title Malaria around large dams in Africa: effect of environmental and transmission endemicity factors
title_full Malaria around large dams in Africa: effect of environmental and transmission endemicity factors
title_fullStr Malaria around large dams in Africa: effect of environmental and transmission endemicity factors
title_full_unstemmed Malaria around large dams in Africa: effect of environmental and transmission endemicity factors
title_short Malaria around large dams in Africa: effect of environmental and transmission endemicity factors
title_sort malaria around large dams in africa effect of environmental and transmission endemicity factors
topic malaria
vector-borne diseases
dams
environmental effects
disease transmission
endemics
mosquitoes
anopheles
breeding habitats
water reservoirs
slope
topography
climatic data
communities
health hazards
url https://hdl.handle.net/10568/105726
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