The information provided here can be used to understand the current situation, increase attention to preterm births in Rwanda and to inform dialogue and action among stakeholders. Data can be used to identify the most important risk factors to target and gaps in care in order to identify and impleme...nt solutions for improved outcomes.
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This profile is part of a series of Climate Risk Country Profiles developed by the World Bank Group (WBG). The country profile
synthesizes most relevant data and information on climate change, disaster risk reduction, and adaptation actions and policies
at the country level. The country profile se...ries are designed as a quick reference source for development practitioners to better
integrate climate resilience in development planning and policy making.
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This Pharmaceutical Country Profile for Kenya (2010) has been developed by the Ministry of Medical Services with support of the World Health Organization. The Profile contains information on existing socio-economic and health-related conditions, resources, regulatory structures and processes and out...comes relating to the pharmaceutical sector in Kenya.
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В настоящем кратком докладе анализируются последние данные о распространенности употребления
табака в Европейском регионе ВОЗ, взятые из доклада о глобальной та...бачной эпидемии за 2017 г., рассматриваются предшествующие аналогичные доклады начиная с 2008 г, а также достижения в деле реализации комплекса мер MPOWER в Европейском регионе. В качестве обоснования используются фактические данные, собранные в «Сборнике аргументов для борьбы против табака». Оценивается прогресс, достигнутый в Европейском регионе ВОЗ в реализации Дорожной карты действий с целью усиления мер по осуществлению Рамочной конвенции ВОЗ по борьбе против табака в Европейском регионе на 2015–2025 гг. (далее – Дорожная карта), и протяженность дальнейшего пути к достижению конечной цели.
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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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Climate change is a major risk to good development outcomes, and the World Bank Group is committed to playing an important role in helping countries integrate climate action into their core development agendas. The World Bank Group is committed to supporting client countries to invest in and build a... low-carbon, climate-resilient future, helping them to be better prepared to adapt to current and future climate impacts.
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…voices of persons with disabilities - Part 1
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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