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Webinar.
The purpose of this booklet is to help readers understand why data on children with disabilities are currently inadequate, the difficulties that surround the gathering of high-quality data on disabled children, and why there is a real need to improve the collection, analysis, dissemination
...
and use of disability data.
more
you can find all 14 Technical Booklets on Inclusive Education, produced by UNICEF, in ENGLISH. Other versions can be found on the website https://www.ded4inclusion.com/inclusive-education-resources-free/unicef-inclusive-education-booklets-and-webinars-english-version. Each Technical Booklet (and com
...
panion webinar) introduces a sub-theme of particular interest within Inclusive Education, and each was written by an expert, and peer-reviewed widely
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In 2018, the Food and Agriculture Organization of the United Nations (FAO) in South Sudan must respond to the highest levels of food insecurity ever recorded in the country. To address this challenge, FAO revised its multiyear Emergency Livelihood Response Programme (ELRP) to enable rapid food produ
...
ction among the most vulnerable communities, protect their livelihoods and reduce dependency on humanitarian aid while building their resilience.
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This report outlines the results of a scientific study of the impacts of weather, climate variability, and climate change on health in Mozambique, with a focus on diarrheal disease and malaria.
Malaria Indicator Survey
DHS Further Analysis Reports No. 109 - This report documents trends in key child nutrition indicators in Rwanda. Data from the Demographic and Health Surveys (DHS) in 2005, 2010, and 2014-15 were analyzed, disaggregated by selected equity-related variables, and tested for trends. Over the survey per
...
iod, Rwanda had high rates of exclusive breastfeeding, with regional variation. Rates of continued breastfeeding were also high but generally decreased as mother’s education and household wealth increased in all survey years. Complementary feeding practices varied by region, mother’s education, household wealth, urban-rural residence, and sex of the child.
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This report investigates the impact of potential misclassification of samples on HIV prevalence estimates for 23 surveys conducted from 2010-2014. In addition to visual inspection of laboratory results, we examined how accounting for potential misclassification of HIV status through Bayesian latent
...
class models affected the prevalence estimates. Two types of Bayesian models were specified: a model that only uses the individual dichotomous test results and a continuous model that uses the quantitative information of the EIA (i.e., the signal-to-cutoff values). Overall, we found that adjusted prevalence estimates matched the surveys’ original results, with overlapping uncertainty intervals. This suggested that misclassification of HIV status should not affect the prevalence estimates in most surveys. However, our analyses suggested that two surveys may be problematic. The prevalence could have been overestimated in the Uganda AIDS Indicator Survey 2011 and the Zambia Demographic and Health Survey 2013-14, although the magnitude of overestimation remains difficult to ascertain. Interpreting results from the Uganda survey is difficult because of the lack of internal quality control and potential violation of the multivariate normality assumption of the continuous Bayesian latent class model. In conclusion, despite the limitations of our latent class models, our analyses suggest that prevalence estimates from most of the surveys reviewed are not affected by sample misclassification.
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