Health Services Insights Volume 10: 1–7
Much remains unknown about displaced communities in out-of-camp areas as identification constraints hinder knowledge on the overall situation and preeminent needs of an area. When compared to regularly monitored in-camp populations, less is known about the health, sanitation, livelihoods, food secur...ity, nutritional status, protection situation, and school attainment of out-of-camp populations.
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The Urban Health Initiative promotes tools and guidance to assess the health impacts of air pollution and the health benefits of sustainable development in energy, transportation, land-use and waste.
Vol. 7, No. 1 (2018) | ISSN 2166-7403 (online) DOI 10.5195/cajgh.2018.295 | http://cajgh.pitt.edu
Health Systems in Transition. Vol. 5 No.3 2015
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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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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Equity and Quality in Health: a People's Right