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
Rashtriya Bal Swasthya Karykram (RBSK). Operational Guidelines
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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Single TB and HIV Concept Note Albania 2016-2018 27 April 2015
Indicators for monitoring the 2016 United Nations Political Declaration on Ending AIDS
UNAIDS supports countries to collect information on their national HIV responses through the Global AIDS Monitoring (GAM) framework—an annual collection of 72 indicators on the response to HIV in a country.... These data form part of the data set used to report back to the General Assembly.
Different from the HIV epidemiological estimates that countries produce for data on the state of the epidemic in a country—that is, data for making estimates on the number of people living with HIV, AIDS-related deaths, etc.—GAM collects information on HIV programmes, including the number of people living with HIV who know their HIV status and people on HIV treatment, and on stigma and discrimination. A full list of the indicators is given in the GAM guidelines.
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UNAIDS 2018, Guidance
Indicators for monitoring the
2016 Political Declaration on Ending AIDS
The report studied child poverty in nine dimensions – development/stunting, nutrition, health, water, sanitation, and housing. Other dimensions included education, health related knowledge, and information and participation.
An estimated 36 million of a total population of 41 million children und...er the age of 18 in Ethiopia are multi-dimensionally poor, meaning they are deprived of basic goods and services in at least three dimensions
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India AIDS Response Report 2014
HIV Testing and Counselling Guidelines