Today, more children than ever before are displaced within their own countries. Their harrowing stories of displacement are unfolding every day, and with increasing frequency. At the end of 2019, approximately 45.7 million people were internally displaced by conflict and violence (Fig. 1.1). Nearly ...half – 19 million – were estimated to be children. And millions more are displaced every year by natural disasters.
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The COVID-19 pandemic has been a formative experience for all humanity and a health emergency of global proportions, presenting a huge challenge to national leaders, health systems, and citizens. The findings of a new report by the OSCE Office for Democratic Institutions and Human Rights (ODIHR) sho...ws that it has also been a test to our democracies and the respect for human rights to which countries across the OSCE committed many years ago.
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A wide range of potential enablers and barriers were identified for influencing progress for the scale-up of severe wasting services within national health systems. Findings were categorised according to the six pillars of WHO’s health system strengthening framework.
This handbook is a quick-reference tool that provides practical, field-level guidance to establish and maintain a GBV sub-cluster in a humanitarian emergency. It provides the foundations for coordination. More in-depth information can be pursued through resources referenced in this handbook. The GBV... AoR website (gbvaor.net) maintains a repository of tools, training materials and resources that complement this handbook. As a second edition, this handbook provides updates to practitioners on humanitarian reforms, lessons learned, promising practices and resources that have emerged since its first publication in 2010.
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Received: 16/11/2013 - Accepted: 23/03/2014 - Published: 27/07/2014
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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Roubles de l’humeur
Chapitre E.4
Edition en français Traduction : Cora Cravero Sous la direction de : David Cohen Avec le soutien de la SFPEADA