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This report explores the complex health challenges induced by climate change in Senegal, from heatwaves to infectious diseases, that jeopardize Sustainable Development Goals (SDGs) particularly SDG 3. It uncovers innovative local strategies in Widou Thiéngoly, offering a glimpse into community-driven solutions that blend climate adaptation and health resilience to pave the way for a coordinated response at COP28 to safeguard vulnerable populations.
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Senegal, a coastal country in the semi-arid Sahel region, faces significant risks associated with climate variability and climate change. Climate change is already affecting vulnerable people’s wellbeing and it’s expected to contribute to the (re)emergence of vector-borne, some water-borne and heat-related diseases, which will have disastrous consequences on the country’s fragile health system and socio-economically vulnerable population. Our contribution to the National Adaptation Plan...
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This epidemiological study was conducted to evaluate the incidence of intestinal and urinary schistosomiasis in children from 6 to 14 years old in the district of Bandafassi of east Senegal. The stools of 505 children from 10 villages were examined. In addition water holes that might serve as biotopes for the intermediate host snails, i.e., Biomphalaria sp. and Bulinus sp., were located and tested. Findings demonstrated the existence of permanent foci of S. mansoni deep within the bush of...
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In Kaédi, a secondary city of Mauritania with approximately 71,000 inhabitants, the analyses of historical climate time series data (1919-2010) and some projections showed a likely occurrence of more frequent heavy rains and higher risks of flooding events in the future. Vulnerability assessments, facilitated through transversal household surveys toward the end of the rainy season that covered the entire city and followed a stratified sampling approach, showed that the community's water...
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Abstract This study aims at enhancing climate data in Senegal using information from the Global Surface Summary of the Day (GSOD). It uses data from 1991 to 2022 from major secondary synoptic stations in Senegal. These data are subject to missing values (data gaps). To address these gaps, multiple imputation was used based on three machine learning models: PMM (Predictive Mean Matching), RF (Random Forest), and NORM (Bayesian Linear Regression). The PMM model relies on averages of similar...
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