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Open Access Highly Accessed Research article

Space-time clustering of childhood malaria at the household level: a dynamic cohort in a Mali village

Jean Gaudart1*, Belco Poudiougou23, Alassane Dicko3, Stéphane Ranque2, Ousmane Toure3, Issaka Sagara3, Mouctar Diallo3, Sory Diawara3, Amed Ouattara3, Mahamadou Diakite3 and Ogobara K Doumbo3*

Author Affiliations

1 Medical Statistics and Informatics Research Team, LIF -UMR 6166- CNRS/Aix-Marseille University, Faculty of Medicine, 27 Bd Jean Moulin 13385 Marseille Cedex 05, France

2 Immunology and Genetics of Parasitic Diseases, UMR 399- INSERM/Aix-Marseille University, Faculty of Medicine, Marseille, France

3 Malaria Research and Training Centre, Department of Epidemiology of Parasitic Diseases, Faculty of Medicine, Pharmacy and Odonto-Stomatology, University of, Bamako, Mali, BP 1805 Bamako, Mali

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BMC Public Health 2006, 6:286  doi:10.1186/1471-2458-6-286

Published: 21 November 2006

Abstract

Background

Spatial and temporal heterogeneities in the risk of malaria have led the WHO to recommend fine-scale stratification of the epidemiological situation, making it possible to set up actions and clinical or basic researches targeting high-risk zones. Before initiating such studies it is necessary to define local patterns of malaria transmission and infection (in time and in space) in order to facilitate selection of the appropriate study population and the intervention allocation. The aim of this study was to identify, spatially and temporally, high-risk zones of malaria, at the household level (resolution of 1 to 3 m).

Methods

This study took place in a Malian village with hyperendemic seasonal transmission as part of Mali-Tulane Tropical Medicine Research Center (NIAID/NIH). The study design was a dynamic cohort (22 surveys, from June 1996 to June 2001) on about 1300 children (<12 years) distributed between 173 households localized by GPS. We used the computed parasitological data to analyzed levels of Plasmodium falciparum, P. malariae and P. ovale infection and P. falciparum gametocyte carriage by means of time series and Kulldorff's scan statistic for space-time cluster detection.

Results

The time series analysis determined that malaria parasitemia (primarily P. falciparum) was persistently present throughout the population with the expected seasonal variability pattern and a downward temporal trend. We identified six high-risk clusters of P. falciparum infection, some of which persisted despite an overall tendency towards a decrease in risk. The first high-risk cluster of P. falciparum infection (rate ratio = 14.161) was detected from September 1996 to October 1996, in the north of the village.

Conclusion

This study showed that, although infection proportions tended to decrease, high-risk zones persisted in the village particularly near temporal backwaters. Analysis of this heterogeneity at the household scale by GIS methods lead to target preventive actions more accurately on the high-risk zones identified. This mapping of malaria risk makes it possible to orient control programs, treating the high-risk zones identified as a matter of priority, and to improve the planning of intervention trials or research studies on malaria.