HIV prevalence in sub-populations with high-risk behavior
The percentage of most-at-risk populations (MARP), including injecting drug users (IDU), men who have sex with men (MSM), and sex workers (SW) and their clients, who have been tested for HIV and have positive test results. The indicator should be calculated separately for each MARP group. For further background on this indicator, see PEPFAR (2009); UNAIDS (2009); WHO/UNICEF/UNAIDS (2011).
This indicator is calculated as:
(Number of members of the MARP group who test positive for HIV/ Total number of members of the MARP group tested for HIV) x 100
This indicator is calculated using data from HIV tests conducted among members of MARP groups in the primary sentinel site (often the capital city) or sites. The sentinel surveillance sites used for the calculation of this indicator should remain constant to allow for the tracking of changes over time. Data should be disaggregated by age groups (<25 years, 25+ years), by sex, MARP group, and where data are available, by prisoners and other vulnerable groups (WHO/UNICEF/UNAIDS, 2011).
Second generation surveillance for HIV (UNAIDS/WHO, 2000); Behavioral surveillance surveys (BSS) and Biological and behavioral surveillance surveys (BBSS) (Family Health International, 2000).
This indicator is used to assess progress on reducing HIV prevalence among MARP groups. It is also useful in countries with concentrated or low-prevalence epidemics, where routine surveillance among pregnant women is not recommended or in countries with concentrated subepidemics within a generalized epidemic. MARP groups typically have the highest HIV prevalence in countries with either concentrated or generalized epidemics. In many cases, the prevalence among these groups can be more than twice the prevalence among the general population. Reducing prevalence among MARP groups is a critical measure of a national-level response to HIV, and therefore, calculating and reporting on HIV prevalence for MARP groups is valuable in identifying patterns and any areas that may require extra attention. Examination of trends with comparable data overtime can demonstrate impact and can be used to inform and monitor programmatic efforts (WHO/UNICEF/UNAIDS, 2011).
Assessing progress in reducing the occurrence of new infections is best done through monitoring changes in incidence over time. However, in practice, prevalence data rather than incidence data are available. In analyzing prevalence data of MARP for the assessment of prevention program impact, it is desirable not to restrict analysis to young people, but to report on those persons who are newly initiated to behaviors that put them at risk for infection. This type of analysis will also have the advantage of not being influenced by the effect of antiretroviral therapy (ART) in increasing survival and thereby increasing prevalence.
The information provided by is indicator may not be nationally representative since it comes only from the handful of jurisdictions surveyed, yet to avoid biases in time trends, data should be reported for the primary sentinel site(s) or capital city only. In recent years, many countries have expanded the number of sentinel sites to include more rural ones, leading to biased trends and lack of comparability. It is possible that individuals will be double counted because they are members of more than one risk group, for example an IDU-SW, since most surveys only target one risk group (WHO/UNICEF/UNAIDS, 2011).
Due to difficulties in accessing MARP, biases in surveillance data are likely to be far more significant than in data from a more general population, such as women attending antenatal clinics. Ideally, the indicator needs to be interpreted with other data (e.g., if available, increase in ART coverage among each sub-group; mixing patterns of the population; general HIV trends) and knowledge on the country context. An understanding of how the sampled population(s) relate to any larger population(s) sharing similar risk behaviors is also critical to the interpretation of this indicator. The period during which people belong to a MARP is more closely associated with the risk of acquiring HIV than age. Therefore, it is desirable not to restrict analysis to young people, but to report on other age groups as well.
Family Health International, 2000, Behavioral surveillance surveys (BSS/BBSS): Guidelines for repeated behavioral surveys in populations at risk for HIV. Arlington, VA, http://www.who.int/hiv/strategic/en/bss_fhi2000.pdf
PEPFAR, 2009, The President’s Emergency Plan for AIDS Relief: Next Generation Indicators Reference Guide, Washington, DC: USAID/PEPFAR. https://www.k4health.org/toolkits/igwg-gender/president%E2%80%99s-emergency-plan-aids-relief-next-generation-indicators-reference
UNAIDS, 2009, Monitoring the Declaration of Commitment on HIV/AIDS: Guidelines on Construction of Core Indicators, Geneva: UNAIDS. http://data.unaids.org/pub/Manual/2009/JC1676_Core_Indicators_2009_en.pdf
UNAIDS, 2008, Methods and assumptions for estimates [website]. Geneva, UNAIDS. (http://www.unaids.org/en/HIV_data/Methodology/default.asp).
WHO and UNAIDS, 2000, Second generation surveillance for HIV: the next decade. Geneva, UNAIDS. (http://www.who.int/hiv/pub/surveillance/en/cds_edc_2000_5.pdf).
WHO/UNICEF/UNAIDS, 2011, A Guide on Indicators for Monitoring and Reporting on the Health Sector Response to HIV/AIDS. Geneva: WHO. http://www.who.int/hiv/data/UA2011_indicator_guide_en.pdf