The Rwandan Ministry of Health recognizes the threat that Non-Communicable Diseases (NCDs) pose to health and development in Rwanda and in 2009 articulates strategies to respond to them in the Health Sector Strategic Plan 2012 - 2018 (HSSP3). Among other things, the plan calls for a national prevale...nce survey on NCD risk factors. This report responds to that call and summarizes the findings of the first NCD risk factor survey in Rwanda conducted from November 2012 to March 2013.
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CBM and the Global Campaign for Education 2014
Testimonies from Humanitarian Workers with Disabilities.
By reading the first-hand accounts, we hear how persons with disabilities, not through any particular talent or skill but from unique knowledge gained through life experience, are ideally placed to provide insights, ideas and leadership, to s...upply essential data, and to fill the gaps in humanitarian response that cause this exclusion.
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Republic of Armenia
Reporting period: January-December 2015
Accessed: 29.09.2019
19 March 2020
Technical documentation
The purpose of this document is to offer guidance to Member States on quarantine measures for individuals in the context of COVID-19. It is intended for those responsible for establishing local or national policy for quarantine of individuals, and adherence ...to infection prevention and control measures.
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Twenty-Fourth Annual Trachoma Control Program Review, Summary Proceedings
…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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