Malaria transmission in Mali is seasonal and peaks at the end of the rainy season in October. This study assessed the seasonal variations in the epidemiology of malaria among children under 10 years of age living in two villages in Selingué: Carrière, located along the Sankarani River but distant from the hydroelectric dam, and Binko, near irrigated rice fields, close to the dam. The aim of this study was to provide baseline data, seasonal pattern and age distribution of malaria incidence in two sites situated close to a lake in Selingué. Geographically, Selingué area is located in the basin of Sakanrani and belongs to the district of Yanfolila in the third administrative region of Mali, Sikasso. Two cross-sectional surveys were conducted in October 2010 (end of transmission season) and in July 2011 (beginning of transmission season) to determine the point prevalence of asymptomatic parasitaemia, and anaemia among the children. Cumulative incidence of malaria per month was determined in a cohort of 549 children through active and passive case detection from November 2010 through October 2011. The number of clinical episodes per year was determined among the children in the cohort. Logistic regression was used to determine risk factors for malaria. The prevalence of malaria parasitaemia varied significantly between villages with a strong seasonality in Carrière (52.0–18.9 % in October 2010 and July 2011, respectively) compared with Binko (29.8–23.8 % in October 2010 and July 2011, respectively). Children 6–9 years old were at least twice more likely to carry parasites than children up to 5 years old. For malaria incidence, 64.8–71.9 % of all children experienced at least one episode of clinical malaria in Binko and Carrière, respectively. The peak incidence was observed between August and October (end of the rainy season), but the incidence remained high until December. Surprisingly, the risk of clinical malaria was two- to nine-fold higher among children 5–9 years old compared to younger children. A shift in the peak of clinical episodes from children under 5–9 years of age calls for expanding control interventions, such as seasonal malaria chemoprophylaxis targeting the peak transmission months.

Mali aims to reach the pre-elimination stage of malaria by the next decade. This study used functional regression models to predict the incidence of malaria as a function of past meteorological patterns to better prevent and to act proactively against impending malaria outbreaks. All data were collected over a five-year period (2012–2017) from 1400 persons who sought treatment at Dangassa’s community health center. Rainfall, temperature, humidity, and wind speed variables were collected. Functional Generalized Spectral Additive Model (FGSAM), Functional Generalized Linear Model (FGLM), and Functional Generalized Kernel Additive Model (FGKAM) were used to predict malaria incidence as a function of the pattern of meteorological indicators over a continuum of the 18 weeks preceding the week of interest. Their respective outcomes were compared in terms of predictive abilities. The results showed that (1) the highest malaria incidence rate occurred in the village 10 to 12 weeks after we observed a pattern of air humidity levels >65%, combined with two or more consecutive rain episodes and a mean wind speed <1.8 m/s; (2) among the three models, the FGLM obtained the best results in terms of prediction; and (3) FGSAM was shown to be a good compromise between FGLM and FGKAM in terms of flexibility and simplicity. The models showed that some meteorological conditions may provide a basis for detection of future outbreaks of malaria. The models developed in this paper are useful for implementing preventive strategies using past meteorological and past malaria incidence.