2 research outputs found

    The contribution of renewable energy technologies to sustainable community development in Rusitu Valley, Zimbabwe

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    Magister Artium (Development Studies) - MA(DVS)This exploratory study is based on the case of the Rusitu Valley, a low income rural community in Zimbabwe. Data was collected using largely qualitative methods and quantitative methods were used to obtain supportive descriptive statistics. Information elicited from focus group discussions conducted with members of the Rusitu Valley community as well as responses obtained from a brief structured questionnaire were used to abstract the Rusitu Valley as a complex adaptive system. Input from in-depth interviews with government representatives in energy policy, local government and non-governmental organisations as well as a review of secondary sources was used to support the analysis and confirm the contextual validity of the study. This study revealed that there is intimate connection between renewable energy technologies and sustainable community development. A key finding was that the contribution of renewable energy technologies in Rusitu Valley is mostly towards the economic dimensions of the community and is relatively limited with regard to social and environmental dimensions. Therefore, this study concluded that renewable energy technologies have not sufficiently contributed towards sustainable community development in the Rusitu Valley. This study also found that the contribution of renewable energy technologies is constrained not only by internal limitations but also external factors. A conclusion drawn from this study was that effective contribution of renewable energy technologies towards social, economic and environmental facets can be enhanced through mainstreaming of renewable energy in policy and planning, as well strengthening institutions and local capacity which would have the overall effect of sustainable community development in low income communitie

    Protocol of an individual participant data meta-analysis to quantify the impact of high ambient temperatures on maternal and child health in Africa (HE 2 AT IPD)

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    Introduction: Globally, recognition is growing of the harmful impacts of high ambient temperatures (heat) on health in pregnant women and children. There remain, however, major evidence gaps on the extent to which heat increases the risks for adverse health outcomes, and how this varies between settings. Evidence gaps are especially large in Africa. We will conduct an individual participant data (IPD) meta-analysis to quantify the impacts of heat on maternal and child health in sub-Saharan Africa. A detailed understanding and quantification of linkages between heat, and maternal and child health is essential for developing solutions to this critical research and policy area. Methods and analysis: We will use IPD from existing, large, longitudinal trial and cohort studies, on pregnant women and children from sub-Saharan Africa. We will systematically identify eligible studies through a mapping review, searching data repositories, and suggestions from experts. IPD will be acquired from data repositories, or through collaboration with data providers. Existing satellite imagery, climate reanalysis data, and station-based weather observations will be used to quantify weather and environmental exposures. IPD will be recoded and harmonised before being linked with climate, environmental, and socioeconomic data by location and time. Adopting a one-stage and two-stage meta-analysis method, analytical models such as time-to-event analysis, generalised additive models, and machine learning approaches will be employed to quantify associations between exposure to heat and adverse maternal and child health outcomes. Ethics and dissemination: The study has been approved by ethics committees. There is minimal risk to study participants. Participant privacy is protected through the anonymisation of data for analysis, secure data transfer and restricted access. Findings will be disseminated through conferences, journal publications, related policy and research fora, and data may be shared in accordance with data sharing policies of the National Institutes of Health. PROSPERO registration number: CRD42022346068
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