BACKGROUND: In sub-Saharan Africa, malaria is a leading cause of morbidity and mortality among young children. Detailed knowledge of spatial variation of malaria epidemiology and associated risk factors is important for planning and evaluating malaria-control measures. METHODS: The spatial variation of malaria incidences and socioeconomic factors were assessed over 21 months, from January 2003 to September 2005, in 535 children from 9 villages of a small rural area with high Plasmodium falciparum transmission in Ghana. Household positions were mapped by use of a global positioning system, and the spatial effects on malaria rates were assessed by means of ecological analyses and bivariate Poisson regression controlling for possible confounding factors. RESULTS: Malaria incidence was surprisingly heterogeneous between villages, and ecological analyses showed strong correlations with village area (R(2) = 0.74; P = .003) and population size (R(2) = 0.68; P = .006). Malaria risk was affected by a number of socioeconomic factors. Poisson regression showed an independent linear rate reduction with increasing distance between children's households and the fringe of the forest. CONCLUSIONS: The exact location of households in villages is an independent and important factor for the variation of malaria incidence in children from high-transmission areas. This fact should be considered in the planning of intervention trials and in spatial targeting of malaria interventions at a local level.
BACKGROUND: In sub-Saharan Africa, malaria is a leading cause of morbidity and mortality among young children. Detailed knowledge of spatial variation of malaria epidemiology and associated risk factors is important for planning and evaluating malaria-control measures. METHODS: The spatial variation of malaria incidences and socioeconomic factors were assessed over 21 months, from January 2003 to September 2005, in 535 children from 9 villages of a small rural area with high Plasmodium falciparum transmission in Ghana. Household positions were mapped by use of a global positioning system, and the spatial effects on malaria rates were assessed by means of ecological analyses and bivariate Poisson regression controlling for possible confounding factors. RESULTS:Malaria incidence was surprisingly heterogeneous between villages, and ecological analyses showed strong correlations with village area (R(2) = 0.74; P = .003) and population size (R(2) = 0.68; P = .006). Malaria risk was affected by a number of socioeconomic factors. Poisson regression showed an independent linear rate reduction with increasing distance between children's households and the fringe of the forest. CONCLUSIONS: The exact location of households in villages is an independent and important factor for the variation of malaria incidence in children from high-transmission areas. This fact should be considered in the planning of intervention trials and in spatial targeting of malaria interventions at a local level.
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