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Key Recommendations for an Inclusive Urban Agenda
GLOBAL EDUCATION MONITORING REPORT 2017/8
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phic and Health Survey
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This report summarizes the findings of the 2010 Rwanda Demographic and Health Survey (RDHS). The 2010 Rwanda Demographic and Health Survey (RDHS) was designed to provide data for monitoring the population and health situation in Rwanda. The 2010 RDHS is the fifth Demographic and Health Survey to be
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conducted in Rwanda (DHS in 1992, 2000, and 2005 and Interim DHS in 2007-08). The objective of the survey was to provide up-to-date information on fertility, family planning, childhood mortality, nutrition including anemia testing, maternal and child health, domestic violence, malaria including malaria testing, maternal mortality, awareness and behavior regarding HIV/AIDS and other sexually transmitted infections, and HIV prevalence.
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DHS Further Analysis Reports No. 108 - This report examines levels, trends, and inequalities in maternal health in Rwanda from 2010 to 2014-15 among women age 15-49 with a recent birth. The analysis uses Demographic and Health Survey (DHS) data for 15 key indicators of maternal health: 6 for antenat
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al care, 3 for delivery, 1 for postnatal care, and 5 for barriers to accessing medical care. Levels and trends in these indicators were analyzed overall and by three background characteristics: women’s education, household wealth quintile, and region.
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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
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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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Report on the nutrition and health situation of Nigeria
Data collection – 13th July to 13th September 2015
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