Many key population groups are hidden, stigmatised and marginalised, and in some settings their behaviours are criminalised. Furthermore individuals in these populations are often highly geographically mobile and can regularly transition between the general population and key population groups.
Tailored approaches are required to estimate the size and dynamics of infection in these groups, their access to treatment and prevention services, and the way that they interact with general populations.
This will enable a better understanding to be gained of the impact individuals in these groups have on wider HIV prevalence and incidence.
What does MeSH aim to do in this area?
|Improve surveillance and program delivery among key populations through the development of HIV prevention cascades, population size estimation, extrapolation and triangulation, and characterising metrics of stigma.|
|Adapt approaches to measure HIV incidence, prevalence, mortality and access to treatment & prevention so that these methods are appropriate for key populations.|
|Develop methods to characterize rates of entry to and exit from these groups and so inform a better understanding of vulnerability at key periods. Examples would be gaining a better understanding of; the age young women first enter sex work or of the heightened risk of HIV transmission for women after they leave formal sex work.|
|Work with stakeholders including major donors, countries with concentrated, mixed and generalized epidemics, civil society and members of key populations to reach consensus on priorities and an accompanying action plan.|
What is MeSH working on and achieved so far?
|A toolkit for the derivation of unique identifiers has been developed that will enable members of key populations to be tracked in order to evaluate the impact of care, treatment and prevention programmes directed towards these groups. This was presented and discussed at a WHO/UNAIDS/Global Fund convened technical expert consultation on strategic information for key populations in March 2016.|
|Metrics that enable a better understanding of how HIV-related stigma operates have been derived. This aim of this is to ensure that a consideration of stigma is an important part of HIV surveillance activities. These metrics have been applied in ongoing research studies and incorporated into UNAIDS guidance tools.|
|A database has been created which synthesises information on key population prevention cascades. We are in the process of populating the database with information from published studies. When complete a user-interface will be developed enabling in-country HIV programme leaders and other stake-holders to make informed decisions on HIV prevention activities based on data from a wide variety of sources.|
|Methodological research has been carried out to estimate HIV intervention coverage among men who have sex with men (MSM) transgender individuals.|
|Operationalising HIV prevention cascades
Building on the theoretical framework provided in the Hargreaves et al paper are activities to operationalise cascades in a number of settings:
• in Zimbabwe, we are focussing on condom distribution and other prevention activities among female sex workers (FSW); also, in our support of the evaluation of DREAMS, we have added specific questions to a survey of vulnerable young women to allow the prevention cascade to be modelled in this group
• in Zambia, we are applying the cascade framework to model the impact of voluntary male medical circumcision
• in Uganda, we are working on developing a prevention cascade focussed on interventions directed toward key populations, and condom distribution programmes directed toward female sex workers
|Population size estimation activities
• In Zimbabwe, our investigations of methods for extrapolating population size estimates from the sub-national to national level to assess intervention coverage among female sex workers provided the foundation for a meeting with the Zimbabwean Ministry of Health in June 2017 on improving the quality of services provided to this group .
• In Haiti, we are developing methods to extrapolate estimates of key population size from municipalities that have data to those that do not to gain national level estimates. This approach is also being applied to estimate the population size of female sex workers, MSM and transgender people in the Dominican Republic.
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