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Malaria around large dams in Africa: effect of environmental and transmission endemicity factors
Open accessAbstract
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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Groundwater seepage can be an important source of larval habitats in other areas, but it is not considered in Default EMOD.
“Groundwater seepage can be an important source of larval habitats in other areas, but it is not considered in Default EMOD.”
From Investigating the Impact of Irrigation on Malaria Vector Larval Habitats and Transmission Using a Hydrology‐Based Model (2023) · cites this paper as Kibret et al., 2019
The Discussion describes groundwater seeping into depressions near reservoirs and creating longer-lived pools that are suitable breeding habitat for malaria mosquitoes. It does not discuss Default EMOD or establish whether that model considers groundwater seepage; searches for EMOD returned no relevant passage. (LLM, conf=0.86)
Experimental — accuracy not yet measuredThe high parasite carriage in Anyakpor and Dwease in 2023 during both dry and rainy seasons is probably due to mining activities and irrigation systems creating breeding sites for Anopheles mosquitoes.
“The high parasite carriage in both dry and rainy season is probably due to the availability of mining activities and irrigation systems in these sites which serve as breading sites and create a conducive environment for the female Anopheles mosquito to reproduce48,49.”
From Reduction in Asymptomatic falciparum malaria infection amongst schoolchildren in three ecological zones of Ghana between 2017 and 2023 (2025) · cites this paper as [48]
The Background (page unavailable) says that dams and associated agricultural activity can create Anopheles breeding habitats, supporting the proposed mechanism in general. The paper does not establish that mining or irrigation caused high parasite carriage in Anyakpor and Dwease in 2023 during both seasons; its Discussion mentions mining water-storage facilities only in the context of impact assessment. (LLM, conf=0.86)
Experimental — accuracy not yet measuredLarval habitats are commonly found in the vicinity of reservoirs where the groundwater level is high and groundwater seeps easily into depressions to form habitats.
“For example, larval habitats are commonly found in the vicinity of reservoirs where the groundwater level is high and groundwater seeps easily into depressions to form habitats (Kibret et al., 2019).”
From Investigating the Impact of Irrigation on Malaria Vector Larval Habitats and Transmission Using a Hydrology‐Based Model (2023) · cites this paper as Kibret et al., 2019
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References 32 · Cited by 38
Research works printed but not linked: 29
- Sadoff CW, Hall JW, Grey D, Aerts JCJH, Ait-Kadi M, Brown C, et al. Securing water, sustaining growth: report of the GWP/OECD task force on water security and sustainable growth. UK: University of Oxford; 2015.
- Union African. Programme for infrastructure development in Africa. Addis Ababa: African Union; 2015.
- Atangana S, Foumbi J, Charlois M, Ambroise-Thomas P, Ripert C. [Epidemiological study of onchocerciasis and malaria in Bamendjin dam area (Cameroon)](in French). Med Trop. 1979;39:537–43.
- Oomen J. Monitoring health in African dams: The Kamburu dam as a test case. Ph.D. Thesis; Rotterdam University. 1981.
- King C. The incorporation of health concerns into African River Basin Planning. MIT Ph.D. thesis, Massachusetts Institute of Technology, Cambridge; 1996.
- Keiser J, Castro MC, Maltese MF, Bos R, Tanner M, Singer BH, et al. Effect of irrigation and large dams on the burden of malaria on a global and regional scale. Am J Trop Med Hyg. 2005;72:392–406. · DOI
- Lautze J, McCartney M, Kirshen P, Olana D, Jayasinghe G, Spielman A. Effect of a large dam on malaria risk: the Koka Reservoir in Ethiopia. Trop Med Int Health. 2007;12:982–9. · DOI
- Yewhalaw D, Legesse W, van Bortel W, Gebre-Silasie S, Kloos H, Duchateau L, et al. Malaria and water resource development: the case of Gilgel-Gibe hydroelectric dam in Ethiopia. Malar J. 2009;8:21. · DOI
- Kibret S, Lautze J, Boelee E, McCartney M. How does an Ethiopian dam increase malaria? Entomological determinants around the Koka Reservoir. Trop Med Int Health. 2012;11:1320–8. · DOI
- Kibret S, Wilson GG, Ryder D, Tekie H, Petros B. Malaria impact of large dams at different eco-epidemiological settings in Ethiopia. Trop Med Health. 2017;5:4. · DOI
- Blanford JI, Blanford S, Crane RG, Mann ME, Paaijmans KP, Schreiber KV, et al. Implications of temperature variation for malaria parasite development across Africa. Sci Rep. 2013;3:1300. · DOI · Paper page
- Abiodun GJ, Maharaj R, Witbooi P, Okosun KO. Modelling the influence of temperature and rainfall on the population dynamics of Anopheles arabiensis. Malar J. 2015;15:364. · DOI
- Cano J, Descalzo MÁ, Moreno M, Chen Z, Nzambo S, Bobuakasi L, et al. Spatial variability in the density, distribution and vectorial capacity of anopheline species in a high transmission village (Equatorial Guinea). Malar J. 2006;5:21. · DOI
- Beck LR, Rodriguez MH, Dister SW, Rodriguez AD, Rejmankova E, Ulloa A, et al. Remote sensing as a landscape epidemiologic tool to identify villages at high risk for malaria transmission. Am J Trop Med Hyg. 1994;51:271–80. · DOI
- Trape JF, Lefebvre-Zante E, Legros F, Ndiaye G, Bouganali H, Druilhe P, et al. Vector density gradients and the epidemiology of urban malaria in Dakar, Senegal. Am J Trop Med Hyg. 1992;47:181–9. · DOI
- Carter R, Mendis KN, Roberts D. Spatial targeting of interventions against malaria. Bull World Health Organ. 2000;78:1401–11.
- Thomas CJ, Cross DE, Bøgh C. Landscape movements of Anopheles gambiae malaria vector mosquitoes in rural Gambia. PLoS ONE. 2013;8:e68679. · DOI
- Kibret S, Wilson GG, Ryder D, Tekie H, Petros B. Environmental and meteorological factors linked to malaria transmission around large dams at three ecological settings in Ethiopia. Malar J. 2019;18:54. · DOI
- Endo N, Eltahir EA. Modelling and observing the role of wind in Anopheles population dynamics around a reservoir. Malar J. 2018;17:48. · DOI
- Jobin W. Dams and disease: ecological design and health impacts of large dams, canals and irrigation systems. London: E&FN Spon; 1999. · DOI
- Endo N, Kiszewski AE, Eltahir EA. Laboratory experiments on stranding of Anopheles larvae under different shoreline environmental conditions. Parasit Vectors. 2015;8:38. · DOI
- Kibret S, Lautze J, McCartney M, Wilson G, Nhamo L. Malaria impact of large dams in sub-Saharan Africa: maps, estimates and predictions. Malar J. 2015;14:339. · DOI
- Kibret S, Lautze J, McCartney M, Nhamo L, Wilson GG. Malaria and large dams in sub-Saharan Africa: future impacts in a changing climate. Malar J. 2016;15:448. · DOI
- WHO. World Malaria Report 2018. Geneva: World Health Organization; 2016.
- Sinka ME, Bangs MJ, Manguin S, Rubio-Palis Y, Chareonviriyaphap T, Coetzee M, et al. A global map of dominant malaria vectors. Parasit Vectors. 2012;5:69. · DOI
- Kauffman C, Briegel H. Flight performance of the malaria vectors Anopheles gambiae and Anopheles atroparvus. J Vector Ecol. 2004;29:140–53.
- Gething PW, Patil AP, Smith DL, Guerra CA, Elyazar IR, Johnston GL, et al. A new world malaria map: Plasmodium falciparum endemicity in 2010. Malar J. 2011;10:378. · DOI
- Moss WJ, Hamapumbu H, Kobayashi T, Shields T, Kamanga A, Clennon J, et al. Use of remote sensing to identify spatial risk factors for malaria in a region of declining transmission: a cross-sectional and longitudinal community survey. Malar J. 2011;10:163. · DOI
- Scudder T. Large dams: long term impacts on riverine communities and free flowing rivers. Singapore: Springer Nature Singapore Pvt Ltd; 2019. · DOI
Metadata
- Authors
- Kibret, S., Lautze, J., McCartney, M., Nhamo, L., & Yan, G.
- Affiliations
- University of California, Irvine (US)
- International Water Management Institute (ZA)
- International Water Management Institute (IWMI) (LK)
- Corresponding author
- Yan, Guiyun
- Venue
- Malaria Journal
- Published
- 2019-09-03
- Volume
- 18
- Issue
- 1
- Pages
- 303-303
- ISSN
- 1475-2875 (ISSN-L)
- PMC
- PMC6720395
- OpenAlex
- W2971432394
- Cited by
- 38
- References
- 32
- Citations by year
- 2025: 10 · 2024: 2 · 2023: 5 · 2022: 4 · 2021: 14 · 2020: 1 · 2019: 2
- FWCI
- 4.83
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Malaria Journal (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- CGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health (U19 AI129326, D43 TW001505, R01 AI050243)
- CGIAR Water Land Ecosystems
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Malaria Research and Control
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mosquito-borne diseases and control
- Social Sciences › Sociology and Political Science › Hydropower, Displacement, Environmental Impact
- Keywords
- malaria, large dams, reservoirs, beach slope, malaria incidence, vulnerable populations, environmental risk factors, sub-Saharan Africa
- MeSH terms
- Humans, Malaria, Water Supply, Incidence, Africa South of the Sahara, Endemic Diseases, Lakes
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