“The children are psychologically crushed and tired.
When we do activities like singing with them, they
don’t respond at all. They don’t laugh like they
would normally. They draw images of children
being butchered in the war, or tanks, or the siege
and the lack of food.”
Teacher in the... besieged town of Madaya to Save the Children
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UNICEF analysis indicates that:
- Investments that increase access to high-impact health and nutrition interventions by poor groups have saved almost twice as many lives as equivalent investments in non-poor groups.
- Access to high-impact health and nutrition interventions has improved ra...pidly among poor groups in recent years, leading to substantial improvements in equity.
- During the period studied, absolute reductions in under-five mortality rates associated with improvements in intervention coverage were three times faster among poor groups than non-poor groups.
- Because birth rates were higher among the poor, the reduction in the under-five mortality rate translated into 4.2 times more lives saved for every 1 million people. Indeed, of the 1.1 million lives saved across the 51 countries during the final year studied for each country, nearly 85 per cent were among the poor.
- Intensified focus on equity-enhancing policies and investments can help countries achieve the Sustainable Development Goal newborn and child mortality targets (SDG3.2).
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The process to develop this "National Traditional Medicine Policy" included a detailed situational analysis of traditional medicine in Liberia and a desk review of relevant documents and the regional policy framework on the alignment of WAHO countries ...policy harmonization.
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Large size: 27 MB. Download directly from the website: https://www.unicef.org/cholera_toolkit/Cholera-Toolkit-2017.pdf
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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The articles in this compendium elaborate on some of the ideas shared at the symposium. Together, they provide a broad view of the dynamic interactions among physical, sexual and brain development that take place during adolescence. They highlight some of the risks to optimal development – includi...ng toxic stress, which can interfere with the formation of brain connections, and other vulnerabilities unique to the onset of puberty and independence. They also point to the opportunities for developing interventions that can build on earlier investments in child development – consolidating gains and even offsetting the effects of deficits and traumas experienced earlier in childhood.
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DHS Methodological Report No. 20
This study used Service Provision Assessment (SPA) and Demographic and Health Survey (DHS) data from Haiti, Malawi, and Tanzania to compare traditionally used additive methods with a data reduction method—principal component analysis (PCA).
We scored ...the quality of health facilities with three approaches (simple additive, weighted additive, and PCA) for two constructs: quality of services, with only facilities-level data, and quality of care, which incorporates observation and client data. We ranked facilities as high, medium, or low quality based on their scores. Our results indicated that the rankings change with the scoring methodology. There was more consistency in the rankings of facilities by the simple additive and PCA methods than the weighted additive and PCA-based rankings. This may be due to the low factor loadings and little variance explained by the first component in the PCA. We aggregated facility scores to their respective DHS clusters (Haiti, Malawi) or regions (Tanzania) and geographically linked them to women interviewed in DHS surveys to test associations between the use of family planning services and the quality environment, as measured with each index.
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Scaling Up Mental Health Care In Rural India
Expanding access to quality health services through task sharing
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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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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