PLoS Negl Trop Dis 16(11): e0010885. https://doi.org/10.1371/journal.pntd.0010885
HAT diagnosis in non-endemic countries is rare and can be challenging, but alertness and
surveillance must be maintained to contribute to WHO’s elimination goals. Early detection is
particularly important as it co...nsiderably improves the prognosis.
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The Lancet Infectious Disease Volume 25, Issue 2e77-e85February 2025
PERC produces regional and member state situation analyses, updated regularly.
The Guidelines on promotive and preventive mental health interventions for adolescents - Helping Adolescents thrive (HAT), provide evidence-informed recommendations on psychosocial interventions to promote mental health, prevent mental disorders, and reduce self-harm and other risk behaviours among ...adolescents.
The HAT Guidelines aims to inform policy development, service planning and the strengthening of health and education systems, and facilitate mainstreaming of adolescent mental health promotion and prevention strategies across sectors and delivery platforms.
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Organizing and Delivering High Quality Care for Chronic Noncommunicable Diseases in the Americas
This document provides interim guidance on the prevention, identification and management of health worker infection in the context of COVID-19. It is intended for occupational health departments, infection prevention and control departments or focal points, health facility administrators and public ...health authorities at both the national and facility level.
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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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PLoS Medicine Vol. 6 no. 10 (2009) e1000165
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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Collection of country-level good practices
Human Resources for Health Observer Series No. 16