UNAIDS 2019, Reference
This edition of UNAIDS data shows the results of some of those successes, but also the challenges that remain. It contains the very latest data on the world’s response to HIV, consolidating a small part of the huge volume o
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f data collected, analysed and refined by UNAIDS over the years. The full data set of information for 1990 to 2018 is available on aidsinfo.unaids.org.
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The indicators and questions in this document are designed for use by national AIDS programmes and partners to assess the state of a country’s
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HIV and AIDS response, and to measure progress towards achieving national HIV targets. Countries are encouraged to integrate these indicators and questions into their ongoing monitoring efforts and to report comprehensive national data through the Global AIDS Monitoring (GAM) process. In this way they will contribute to improving understanding of the global response to the HIV epidemic, including progress that has been made towards achieving the commitments and global targets set out in the new United Nations Political Declaration on HIV and AIDS: Ending Inequalities and Getting on Track to End AIDS by 2030, adopted in June 2021, and the linked Sustainable Development Goals.
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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 M
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onitoring (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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Biennial Report. SUBMITTED TO THE UNITED NATIONS GENERAL ASSEMBLY SPECIAL SESSION ON HIV AND AIDS
Reporting period: January 2012 – December 2013
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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 resu
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lts, 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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UNAIDS/99.31E (English original, June 1999)
1st revision, April 2000
Participant Manual
February 2011
Edition 3.0
Summary Report
Accessed: 19.10.2019
The National AIDS Control Council (NACC) continues to strengthen partnerships with all stakeholders in the response to HIV and
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AIDS in Kenya. While recognizing that there is no single preventive approach to reverse the spread of HIV, the faith sector comprising of Faith Communities (FCs) and Faith-Based Organizations (FBOs) have demonstrated sustained motivation and moral authority with resources and outreach capability to significantly reduce new HIV infections. In addition, they have the power to influence policy changes to address societal, cultural and structural factors that impede individuals’ capacity to prevent HIV infection. According to Kenya Demographic Health Survey (2014), over 97% of the Kenya population was reported to ascribe to religious affiliation.
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The LDHS provides an opportunity to inform policy and provide data for planning, implementation, and monitoring and evaluation of national health p
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rograms. It is designed to provide up-to-date information on health indicators including fertility levels, sexual activity, fertility preferences, awareness and use of family
planning methods, breastfeeding practices, nutritional status of children, early childhood and maternal mortality, maternal and child health, and awareness and behaviors regarding HIV/AIDS and other sexually transmitted infections. The study also incorporated measurements of HIV, hepatitis B, and hepatitis Cprevalence along with seroprevalence of Ebola virus disease antibodies, the results of which will be included in future addendums. In addition to presenting national estimates, the report provides estimates of key indicators for both rural and urban areas, the country’s 15 counties, and the capital, Monrovia.
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Participant Manual September 2012
Surveillance of Populations at High Risk for HIV Transmission