Mahamadou Diakite

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). 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. 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. 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.

Summary: Background  Modelling malaria parasitaemia as function of fever has been proposed as best alternative to estimate the attributable fraction of malaria fever and the sensitivity and specificity of different case definitions of malaria disease.Objectives  To determine the prevalence of fever and its relation to malaria parasitaemia and to establish a pyrogenic threshold for malaria disease in the area.Methods  We conducted two cross‐sectional surveys in children of 6 months to 9 years of age (2434 during the rainy season of 1993 and 2353 during the dry season of 1994) randomly selected from 21 areas of Bandiagara district, Mali.Results  The relationship between fever and Plasmodium falciparum parasitaemia depends strongly on the season, thus affecting the malaria‐attributable fraction of fever cases and the sensitivity and specificity of malaria case definitions. The overall proportion of fever attributable to malaria parasitaemia was 33.6% during the rainy season and 23.3% during the dry season, with the highest proportion occurring among the youngest children. The cut‐off value, where the sensitivity curve crosses the specificity curve, was around 3200 pf/μl for all age categories during the rainy season and 200 pf/μl during the dry season.Conclusions  Malaria remains a main cause of fever in this area of Mali. The pyrogenic threshold of parasitaemia depends strongly on the season, and different cut‐off levels of parasitaemia should be used during the two seasons to define malaria cases in this area.