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A case-control study examined vector-related and environmental parameters associated with severe malaria in Kilifi District along the coast of Kenya. Over an 11-month period, 119 children identified with severe malaria infections at the Kilifi District Hospital were matched by age with control children who reported to the outpatient clinic with nonsevere infections. Intensive mosquito sampling was done in each of the case-control houses over a four-day period, beginning within a week of index case admission. A total of 109 environmental, demographic, behavioral, and animal husbandry variables were characterized for each household. Vector species (Anopheles gambiae s.l. and An. funestus) were detected in 40.1% and 36.1% of case and control houses, respectively. The relative abundance of vectors in individual houses was stable over the two-week resampling periods (r = 0.9). Both the overall abundance of anopheline mosquitoes (odds ratio [OR] = 1.5) and P. falciparum sporozoite rates (OR = 1.5) were not significantly different between case and control houses. In a matched analysis, 11 of 109 house variables associated significantly with severe malaria were also associated with vector abundance, as determined by chi-square linear trend analysis. Under conditions of year-round, low-level transmission on the coast of Kenya, the risk of severe disease in children is multifactorial and not governed strictly by transmission intensity or environmental heterogeneity affecting vector abundance and distributions. This suggests that current interventions that appear to be achievable only in areas where transmission is already low to moderate should be appropriate. However, such interventions should be monitored so that inappropriate and possibly disastrous control activities can be avoided in Africa.

Type

Journal article

Journal

Am J Trop Med Hyg

Publication Date

05/1999

Volume

60

Pages

781 - 785

Keywords

Animals, Anopheles, Case-Control Studies, Child, Preschool, Housing, Humans, Infant, Infant, Newborn, Insect Vectors, Kenya, Malaria, Falciparum, Plasmodium falciparum, Population Density, Regression Analysis, Risk Factors