Medicine (RMH) - Research Publications

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Author: Diouf, Ibrahima × End date: 2019 × Start date: 2015 ×

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    Sero-epidemiological evaluation of Plasmodium falciparum malaria in Senegal
    Sylla, K ; Tine, RCK ; Ndiaye, M ; Sow, D ; Sarr, A ; Mbuyi, MLT ; Diouf, I ; Lo, AC ; Abiola, A ; Seck, MC ; Ndiaye, M ; Badiane, AS ; N'Diaye, JLA ; Ndiaye, D ; Faye, O ; Dieng, T ; Dieng, Y ; Ndir, O ; Gaye, O ; Faye, B (BMC, 2015-07-16)
    BACKGROUND: In Senegal, a significant decrease of malaria transmission intensity has been noted the last years. Parasitaemia has become lower and, therefore, more difficult to detect by microscopy. In the context of submicroscopic parasitaemia, it has become relevant to rely on relevant malaria surveillance tools to better document malaria epidemiology in such settings. Serological markers have been proposed as an essential tool for malaria surveillance. This study aimed to evaluate the sero-epidemiological situation of Plasmodium falciparum malaria in two sentinel sites in Senegal. METHODS: Cross-sectional surveys were carried out in Velingara (south Senegal) and Keur Soce (central Senegal) between September and October 2010. Children under 10 years old, living in these areas, were enrolled using two-level, random sampling methods. P. falciparum infection was diagnosed using microscopy. P. falciparum antibodies against circumsporozoite protein (CSP), apical membrane protein (AMA1) and merozoite surface protein 1_42 (MSP1_42) were measured by ELISA method. A stepwise logistic regression analysis was done to assess factors associated with P. falciparum antibodies carriage. RESULTS: A total of 1,865 children under 10 years old were enrolled. The overall falciparum malaria prevalence was 4.99% with high prevalence in Velingara of 10.03% compared to Keur Soce of 0.3%. Symptomatic malaria cases (fever associated with parasitaemia) represented 17.37%. Seroprevalence of anti-AMA1, anti-MSP1_42 and anti-CSP antibody was 38.12, 41.55 and 40.38%, respectively. The seroprevalence was more important in Velingara and increased with age, active malaria infection and area of residence. CONCLUSION: The use of serological markers can contribute to improved malaria surveillance in areas with declining malaria transmission. This study provided useful baseline information about the sero-epidemiological situation of malaria in Senegal and can contribute to the identification of malaria hot spots in order to concentrate intervention efforts. TRIAL REGISTRATION NUMBER: PACTR201305000551876 ( http://www.pactr.org ).
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    Comparison of Malaria Simulations Driven by Meteorological Observations and Reanalysis Products in Senegal
    Diouf, I ; Rodriguez-Fonseca, B ; Deme, A ; Caminade, C ; Morse, AP ; Cisse, M ; Sy, I ; Dia, I ; Ermert, V ; Ndione, J-A ; Gaye, AT (MDPI, 2017-10)
    The analysis of the spatial and temporal variability of climate parameters is crucial to study the impact of climate-sensitive vector-borne diseases such as malaria. The use of malaria models is an alternative way of producing potential malaria historical data for Senegal due to the lack of reliable observations for malaria outbreaks over a long time period. Consequently, here we use the Liverpool Malaria Model (LMM), driven by different climatic datasets, in order to study and validate simulated malaria parameters over Senegal. The findings confirm that the risk of malaria transmission is mainly linked to climate variables such as rainfall and temperature as well as specific landscape characteristics. For the whole of Senegal, a lag of two months is generally observed between the peak of rainfall in August and the maximum number of reported malaria cases in October. The malaria transmission season usually takes place from September to November, corresponding to the second peak of temperature occurring in October. Observed malaria data from the Programme National de Lutte contre le Paludisme (PNLP, National Malaria control Programme in Senegal) and outputs from the meteorological data used in this study were compared. The malaria model outputs present some consistencies with observed malaria dynamics over Senegal, and further allow the exploration of simulations performed with reanalysis data sets over a longer time period. The simulated malaria risk significantly decreased during the 1970s and 1980s over Senegal. This result is consistent with the observed decrease of malaria vectors and malaria cases reported by field entomologists and clinicians in the literature. The main differences between model outputs and observations regard amplitude, but can be related not only to reanalysis deficiencies but also to other environmental and socio-economic factors that are not included in this mechanistic malaria model framework. The present study can be considered as a validation of the reliability of reanalysis to be used as inputs for the calculation of malaria parameters in the Sahel using dynamical malaria models.