© 1998 Oxford University Press
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An analysis of the geographical distribution of severe malaria in children in Kilifi District, Kenya
aTropical Health Epidemiology Unit, London School of Hygiene and Tropical Medicine Keppel Street, London WC1E 7HT, UK
bClinical Research Centre, Kilifi Unit, Kenya Medical Research Institute PO Box 230, Kilifi, Kenya
cNuffield Department of Clinical Medicine, University of Oxford Oxford OX3 99D, UK
Reprint requests: Joanna Armstrong Schellenberg. Ifakara Centre, PO Box 53, Ifakara, Tanzania
BACKGROUND: Although malaria is known to be a major cause of child mortality and morbidity throughout sub-Saharan Africa there are few detailed studies of malaria mortality rates and incidence of severe malarial disease in defined communities. We have studied the geographical pattern of admissions to hospital with severe malaria and the stability of this pattern over time in Kilifi District on the Kenyan Coast.
METHODS: Over a 2-year period all children under 5 years of age with severe malaria admitted to the district hospital and living in a rural study population of about 50 000 people were identified. Annual censuses were carried out in the study area, and all households were mapped using a hand-held satellite navigation system. The resulting databases were linked using a geographical information system (GIS).
RESULTS: Using methods originally developed for the study of the geographical distribution of childhood leukaemia we assessed the spatial pattern of hospital admission rates for severe malaria. As expected, admission rates were significantly higher in children with easier access to the hospital. For example, those living more than 25 km from the hospital had admission rates which were about one-fifth of those for children living within 5 km of the hospital. Those living more than 2.5 km from the nearest road had admission rates that were about half of those for children living within 0.5 km of a road. We also investigated short-term local fluctuations in severe malaria and found evidence of space-time dusterin of severe malaria.
CONCLUSIONS: Hospital admission rates for severe malaria are higher in households with better access to hospital than in those further away. The finding of space-time clusters of severe malaria suggests that it would be of value to conduct case-control studies of environmental, genetic and human behavioural factors involved in the aetiology of the disease.
Keywords Severe malaria, Kenya, geographical information system, mapping, spatial pattern, space-time clustering
Accepted 23 May 1997
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