Minakawa N, Mutero CM, Githure JI, Beier JC, Yan G, 1999. Spatial distribution and habitat characterization of anopheline mosquito larvae in western Kenya. Am J Trop Med Hyg 61 :1010–1016.
Gimnig JE, Ombok M, Kamau L, Hawley WA, 2001. Characteristics of larval anopheline (Diptera: Culicidae) habitats in western Kenya. J Med Entomol 38 :282–288.
Robert V, Awono-Ambene HP, Thioulouse J, 1998. Ecology of larval mosquito, with special reference to Anopheles arabiensis (Diptera: Culicidae) in market-garden wells in the urban area of Dakar, Senegal. J Med Entomol 35 :948–955.
Trape JF, Zoulani A, 1987. Malaria and urbanization in central Africa: the example of Brazzaville. Part II: Results of entomological surveys and epidemiological analysis. Trans R Soc Trop Med Hyg 81 :10–18.
Khaemba BM, Mutani A, Bett MK, 1994. Studies on the anopheline mosquitoes transmitting malaria in a newly developed highland urban area: a case study of Moi University and its environs. East Afr Med J 71 :159–164.
Chinery WA, 1984. Effects of ecological changes on the malaria vectors Anopheles funestus and the Anopheles gambiae complex of mosquitoes in Accra, Ghana. J Trop Med Hyg 87 :75–81.
Barbazan P, Baldet T, Darriet F, Escaffre H, Djoda DH, Hougard JM, 1998. Impact of treatments with Bacillus sphaericus on Anopheles populations and the transmission of malaria in Maroua, a large city in a savannah region of Cameroon. J Am Mosq Control Assoc 14 :33–39.
Coene J, 1993. Malaria in urban and rural Kinshasa: the entomological input. Med Vet Entomol 7 :127–137.
Gillies MT, Coetzee M, 1987. A Supplement to the Anopheline of Africa South of the Sahara (Afrotropical Region). Johannesburg, South Africa: South African Institute for Medical Research. Publication no. 55.
Gillies MT, DeMeillon B, 1968. The Anopheline of Africa South of the Sahara (Ethiopian Zoogeographical Region). Johannesburg, South Africa: (South African Institute for Medical Research.
Mendis C, Jacobsen JL, Gamage-Mendis A, Bule E, Dgedge M, Thompson R, Cuamba N, Barreto J, Begtrup K, Sinden RE, Hogh B, 2000. Anopheles arabiensis and An. funestus are equally important vectors of malaria in Matola coastal suburb of Maputo, southern Mozambique. Med Vet Entomol 14 :171–180.
Kenya National Bureau of Statistics, 1999. Executive Report: Summary Statistics. Nairobi, Kenya.
Githeko AK, Service MW, Mbogo CM, Atieli F, Juma FO, 1993. Plasmodium falciparum sporozoite and entomological inoculation rates at the Ahero rice irrigation scheme and the Miwani sugar-belt in western Kenya. Ann Trop Med Parasitol 87 :379–391.
Petrarca V, Beier JC, 1992. Intraspecific chromosomal polymorphism in the Anopheles gambiae complex as a factor affecting malaria transmission in the Kisumu area of Kenya. Am J Trop Med Hyg 46 :229–237.
Mbogo CM, Snow RW, Khamala CP, Kabiru EW, Ouma JH, Githure JI, Marsh K, Beier JC, 1995. Relationships between of Plasmodium falciparum transmission by vector populations and the incidence of severe disease at nine sites on the Kenyan coast. Am J Trop Med Hyg 52 :201–206.
Schneider DC, 1994. Quantitative Ecology. New York: Academic Press.
Mendenhall W, Sincich T, 1996. A Second Course in Statistics: Regression Analysis. Englewood Cliffs, NJ: Prentice-Hall, Inc.
Sudman S, 1978. Applied Sampling. New York: Academic Press.
Service MW, 1976. Mosquito Ecology. New York: John Wiley and Sons Publishing.
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This paper describes a geographic sampling strategy for ecologic studies and describes the relationship between human activities and anopheline larval ecology in urban areas. Kisumu and Malindi, Kenya were mapped using global positioning systems, and a geographic information system was used to overlay a measured grid, which served as a sampling frame. Grid cells were stratified and randomly selected according to levels of planning and drainage. A cross-sectional survey was conducted in April and May 2001 to collect entomologic and human ecologic data. Multivariate regression analysis was used to test the relationship between the abundance of potential larval habitats, and house density, socioeconomic status, and planning and drainage. In Kisumu, 98 aquatic habitats were identified, 65% of which were human made and 39% were positive for anopheline larvae. In Malindi, 91 aquatic habitats were identified, of which, 93% were human made and 65% were harboring anopheline larvae. The regression model explains 82% of the variance associated with the abundance of potential larval habitats in Kisumu. In Malindi, 59% of the variance was explained. As the number of households increased, the number of larval habitats increased correspondingly to a point. Beyond a critical threshold, the density of households appeared to suppress the development of aquatic habitats. The proportion of high-income households and the planning and drainage variables tested insignificant in both locations. The integration of social and biologic sciences will allow local mosquito and malaria control groups an opportunity to assess the risk of encountering potentially infectious mosquitoes in a given area, and concentrate resources accordingly.