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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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
Impact Evalution Report 61
Accessed online August 2018
Accessed online August 2018
Accessed online August 2018
Data from the 2011 Ethiopia Demographic and Health Survey
Accessed online August 2018
Challenges and Opportunities. This report presents a comprehensive assessment of the education and labor markets for nurses in the ECSA region. It documents the main challenges to train and deploy nurses and discusses opportunities for government and private sector employers to overcome these chall...enges. The report provides empirical evidence to support the expansion of nursing education within the region with a focus on private sector engagement, effective labor market regulation, and regional collaboration. A regional focus for investment may be necessary to create enough potential deals, reduce individual country and regulatory risks, encourage good private institutions to move across borders within the region, and seek to create regional standards for regulation.
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The brief on key findings from the 2025 edition of the WHO anaemia estimates provides a snapshot of the current status of anaemia among women aged 15–49 years at the country, regional, and global levels, along with progress toward achieving the global anaemia target by 2030, in alignment with the ...Sustainable Development Goals.
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