The Countdown country profile presents in one place the best and latest evidence to enable an assessment of a country’s progress in improving reproductive, maternal, newborn, and child health (RMNCH)
Une mission d’appui regroupant des experts diligentés par l’OMS Genève s’est rendue au Bénin du 17 au 24 novembre 2014 pour aider le pays dans la mise en place de son plan de prévention et de riposte à une éventuelle épidémie de maladie à virus Ebola.
Dans ce rapport la mission esti...me que la situation actuelle du pays, caractérisée par une épidémie confirmée de fièvre de Lassa et la préparation de la riposte à la maladie à virus Ebola (MVE) demande, d’une part, l’organisation d’une riposte adéquate et d’autre part, un changement de paradigme. Concrètement, en mettant en place un dispositif comme si le pays se trouvait face à son premier cas de MVE plutôt qu’une préparation en l’absence de cas.
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This year marked the beginning of the WHO biennium 2016-2017 action plan; this annual report highlights WHO’s key achievements in 2016
It also documents the extraordinary efforts by a broad coalition of government ministries, municipalities, international agencies, community groups, women’s or...ganizations, religious and traditional leaders, media, private sector and donors towards restoration and improving health indicators.
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Policy brief. HIV testing services (HTS) and anti-retroviral therapy (ART) have been scaled up substantially. It is estimated that, globally, nearly 80% of people with HIV now know their status. With the offer of immediate ART initiation and improved treatment options, access to and uptake of treatm...ent have increased, too. Now, most people with HIV who know their status are obtaining treatment and care.
In response to these changes in the global HIV epidemic, WHO is encouraging countries to use three consecutive reactive tests for an HIV-positive diagnosis as their treatment-adjusted prevalence and national HTS positivity fall below 5% .
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The 2013 RMIS is a nationally representative, household-based survey that provides data on malaria indicators, which are used to assess the progress of a malaria control program. The primary objective of the 2013 Rwanda Malaria Indicator Survey (2013 RMIS) was to provide up-to date information on th...e prevention of malaria to policymakers, planners, and researchers.
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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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The Countdown country profile presents in one place the best and latest evidence to enable an assessment of a country’s progress in improving reproductive, maternal, newborn, and child health (RMNCH)
The Countdown country profile presents in one place the best and latest evidence to enable an assessment of a country’s progress in improving reproductive, maternal, newborn, and child health (RMNCH)
The Countdown country profile presents in one place the best and latest evidence to enable an assessment of a country’s progress in improving reproductive, maternal, newborn, and child health (RMNCH)
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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