The Republic of the Union of Myanmar’s National Strategic Plan on HIV/AIDS 2016–2020 is the strategic guide for the country’s response to HIV at national, state/regional and local levels. The framework describes the current dynamics of the HIV epidemic and articulates a strategy to optimize in...vestments through a fast track approach with the vision of ending HIV as a public health threat by 2030. Myanmar’s third National Strategic Plan (HIV NSP III) issues a call to all partners to front-load investments to close the testing gap and reach the 90–90–90 prevention and treatment targets to protect health for all.
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Northern: Chandigarh, Delhi, Haryana, Himachal Pradesh, Jammu & Kashmir, Punjab, Rajasthan, and Uttarakhand
Central: Chhattisgarh, Madhya Pradesh and Uttar Pradesh
Eastern: Andaman & Nicobar, Bihar, Jharkhand, Odisha and West Bengal
This technical document consists of epidemiological ...profiles (fact-sheets) for States and districts based on information available from multiple data sources including the HIV Sentinel Surveillance (HSS) and the Integrated Biological and Behavioural Surveillance (IBBS). Given the need for focussed prevention efforts in low/high prevalence and vulnerable States/districts, the information presented will be useful for policy makers, program planners at national/State/ district level, researchers, and academicians in identification of areas for priority attention and also to derive meaningful conclusions for programme planning, implementation, monitoring and scale-up. This document will be a quick reference for the HIV/AIDS situation in a State/district, risk and safe behaviour of the high risk groups, their level of knowledge about STIs and HIV/AIDS, experience of violence, HIV testing and ART awareness and exposure to HIV/AIDS prevention.
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West: Drada & Nagar Haveli, Daman & Diu, Goa, Gujarat, Maharashtra
South: Andhra Pradesh & Telangana, Karnataka, Kerala, Puducherry, Tamil Nadu
This technical document consists of epidemiological profiles (fact-sheets) for States and districts based on information available from multiple d...ata sources including the HIV Sentinel Surveillance (HSS) and the Integrated Biological and Behavioural Surveillance (IBBS). Given the need for focussed prevention efforts in low/high prevalence and vulnerable States/districts, the information presented will be useful for policy makers, program planners at national/State/ district level, researchers, and academicians in identification of areas for priority attention and also to derive meaningful conclusions for programme planning, implementation, monitoring and scale-up. This document will be a quick reference for the HIV/AIDS situation in a State/district, risk and safe behaviour of the high risk groups, their level of knowledge about STIs and HIV/AIDS, experience of violence, HIV testing and ART awareness and exposure to HIV/AIDS prevention.
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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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This report describes the work done by WHO from January 2015 up to the end of December 2016 to address the long-term issues of survivor care, health-systems strengthening and research.
Haïti: DHS 2016-2017 - Key Indicators Report (French)
Ce manuel donne une vue d’ensemble des connaissances scientifiques actuelles sur l’infection à VIH ainsi que des technologies et des outils utilisés pour prévenir cette infection, pour améliorer la qualité de vie des personnes infectées et pour réduire les effets du VIH sur les enfants et... leur famille. Le manuel présente aussi les stratégies nécessaires pour atteindre les personnes ayant besoin de ces interventions et définit leurs normes.
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Pre-Publication draft version. Lat reviewed on 7th July 2017
The END TB Strategy
Интеграция совместного оказания услуг в связи с ТБ и ВИЧ во всеобъемлющий пакет помощи для потребителей инъекционных наркотиков