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The main objective of this study is to analyze the effect of political instability on youths unemployment in sub‐Saharan Africa. Particular interest is devoted to the channels through which political instability affects youths unemployment. The empirical analysis covers a sample of 23 countries for the period 2000–2016. To better characterize the labor market framework in sub‐Saharan Africa, the empirical analysis incorporates the impact of political instability on youths underemployment and labor underutilization. Using panel data techniques, the results show that political instability increases youths unemployment, underemployment, and labor underutilization in sub‐Saharan Africa. The main transmission channels identified are foreign direct investment, domestic investment, gross domestic product, government spending, human capital, and labor market flexibility. The findings confirm the investigated hypothesis. As the main policy implication, policymakers in sub‐Saharan Africa should resolve political instability as a priority toward addressing youths unemployment. [ABSTRACT FROM AUTHOR]

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This work is devoted to the experimental study of banana drying energy consumption. A prototype drier with a capacity of 120 kg fresh products, meeting the needs of a producer, was designed and built. The system was then used to undertake an experimental study on energy consumption of banana drying, taking into account the influence of the aerodynamic settings within the drying enclosure. The results showed that the final sought water content, approximately 20%, dry basis, is obtained in 35 hours when drying is made at 60°C without recirculation of air; the power consumption was 83 kwh. The power consumption was lower (only 30 kWh) if drying at lower temperatures (40°C) was combined to air recirculation during the process. The combination of the aerodynamic settings would therefore make it possible to practically divide the energy drying consummation by three; this against a relatively longer operation time (65 hours). This result brings an interesting indicator on the energy constraints related to this type of processing for banana conservation, a strongly perishable product with great importance for the economy of Subsaharan African countries in particular. [ABSTRACT FROM AUTHOR]

• In this work, the main objective is the implementation of an energy conservation. • Corresponding to 174 solar panels, 9 wind turbines, 1 micro hydro generator. • Simulation results showed that considerable savings were made. • The results also indicate that the best configurations are all cost-efficient. This paper presents an optimal design and selection made on four energy systems or configurations with criteria Loss of Power Supply Probability, Cost of Energy, Total Emission and the Diesel Contribution Factor using a Multi-objective Particle Swarm Optimization technique; for some rural communities selected from five different countries in the Sub-Saharan Africa region. These communities include BOGO, BOGOMORO, DANTIKA, GARA-ALI and KASSOUALA. Energy conservation demand-side management strategy is also applied in this study. The results obtained reveal that considerable savings are made with the demand-side management strategy and that Configuration 1 with demand-side management is the best energy system for the communities of BOGO, GARA-ALI and KASSOUALA; Configuration 2 with demand-side management is the best energy system for the communities of DANTIKA and BOGOMORO. For the case of BOGO, the best configuration consists of 196 solar panels, 10 wind turbines, 1 micro hydro generator, 1.5 days of storage system autonomy and 1 diesel generator with Cost of Energy 0.096 $/kWh, 15080.47 kg of Total Emission and 0.0002% of Diesel Contribution Factor. In DANTIKA, the best configuration 174 solar panels, 9 wind turbines, 1 micro hydro generator, 1.3 days of storage system autonomy with Cost of Energy 0.088 $/kWh and 10524.474 kg of Total Emission. Moreover, the results of this study can provide a good framework in the development of Hybrid renewable energy systems to solve the problem of energy deficit in poor rural communities. [ABSTRACT FROM AUTHOR]

Summary Background Schistosomiasis affects more than 200 million individuals, mostly in sub-Saharan Africa, but empirical estimates of the disease burden in this region are unavailable. We used geostatistical modelling to produce high-resolution risk estimates of infection with Schistosoma spp and of the number of doses of praziquantel treatment needed to prevent morbidity at different administrative levels in 44 countries. Methods We did a systematic review to identify surveys including schistosomiasis prevalence data in sub-Saharan Africa via PubMed, ISI Web of Science, and African Journals Online, from inception to May 2, 2014, with no restriction of language, survey date, or study design. We used Bayesian geostatistical meta-analysis and rigorous variable selection to predict infection risk over a grid of 1 155 818 pixels at 5 × 5 km, on the basis of environmental and socioeconomic predictors and to calculate the number of doses of praziquantel needed for prevention of morbidity. Findings The literature search identified Schistosoma haematobium and Schistosoma mansoni surveys done in, respectively, 9318 and 9140 unique locations. Infection risk decreased from 2000 onwards, yet estimates suggest that 163 million (95% Bayesian credible interval [CrI] 155 million to 172 million; 18·5%, 17·6–19·5) of the sub-Saharan African population was infected in 2012. Mozambique had the highest prevalence of schistosomiasis in school-aged children (52·8%, 95% CrI 48·7–57·8). Low-risk countries (prevalence among school-aged children lower than 10%) included Burundi, Equatorial Guinea, Eritrea, and Rwanda. The numbers of doses of praziquantel needed per year were estimated to be 123 million (95% CrI 121 million to 125 million) for school-aged children and 247 million (239 million to 256 million) for the entire population. Interpretation Our results will inform policy makers about the number of treatments needed at different levels and will guide the spatial targeting of schistosomiasis control interventions. Funding European Research Council, China Scholarship Council, UBS Optimus Foundation, and Swiss National Science Foundation. [ABSTRACT FROM AUTHOR]