A database of the epidemiological data that drive the programming and policy decisions of the largest funders of Key Populations HIV programming globally and the funding decisions they make in response.
Inequities in society have long created disparities in how, when, and which people are able to access health care services. The history of the HIV epidemic globally is rife with examples of disparities in access to HIV testing services, prevention tools, and care & treatment with marginalized and stigmatized groups accessing services later and at lower rates. Inequitable access to these services remains at the heart of why HIV continues to affect different populations differently. For members of key populations, these inequities stem from stigma, discrimination, violence, criminalization, and insufficient funding for programming targeting the specific needs of these communities. Key populations are defined as men who have sex with men (MSM), sex workers (SW), people who inject drugs (PWID), and transgender people (TG), based on international standards and disproportionate impact of HIV on these communities. Globally, 43% of new HIV infections in 2019 are estimated to have been among these populations and a further 19% to be among their sexual partners despite key populations making up a much smaller proportion of the total population. Consequentially, HIV prevalence rates among members of these groups are also much higher. Yet HIV treatment outcomes and services consistently lag behind services delivered to other populations.
To end HIV as a global public health threat, tackling the inequities that disproportionately affect key populations is not optional. Improving access to testing, prevention, treatment and other services for key populations, however, can only happen if funding and policy decisions are aligned to address these needs and based on high quality data. Major funders of the global HIV response, including the President's Emergency Plan for AIDS Relief (PEPFAR) and the Global Fund to Fight AIDS, Tuberculosis, and Malaria (Global Fund or GF) have long emphasized the importance of programming targeting key populations, but dynamics of these programs - who is being funded, what work they are funded to do, how communities are consulted and participate, what data are driving the decisions, and the relative size of the funding compared to other investments - is challenging to both access and assess. Inequitable access to these data undermine the ability for communities of key populations to themselves engage directly with those tasked with implementing key population programming and developing accountability mechanisms such as community-led monitoring to ensure programming is delivering as intended.
There is a substantial gap between the language and the intentions that funders of the global HIV response like PEPFAR and The Global Fund use and have for key populations within the broader fight against HIV and the transparency of information they provide to the communities of key populations who should be both the beneficiaries of that programming as well as the primary developers, designers, implementers, and accountability monitors of that programming. But the data that funders use to determine their financial allocations for key populations are difficult to identify. Moreover, basic information such as who is being funded to implement key populations programming, what they are being funded to do precisely, and where they are funded to work remain difficult to find. The goal of this database is to bring together these pieces of information - sourced from the funders themselves - to show the data behind the funding decisions that are being made and who the recipients of that funding are to the best of our ability. To that end, this database combines:
In providing this information, we hope to help close the gap between the largest funders of global HIV key populations programming and the communities, civil society organizations, researchers, academics, journalists, and others who need better access to this information to follow-up and hold duty-bearers accountable for the implementation of programs.
Inequities in society have long created disparities in how, when, and which people are able to access health care services. The history of the HIV epidemic globally is rife with examples of disparities in access to HIV testing services, prevention tools, and care & treatment with marginalized and stigmatized groups accessing services later and at lower rates. Inequitable access to these services remains at the heart of why HIV continues to affect different populations differently. For members of key populations, these inequities stem from stigma, discrimination, violence, criminalization, and insufficient funding for programming targeting the specific needs of these communities. Key populations are defined as men who have sex with men (MSM), sex workers (SW), people who inject drugs (PWID)*, and transgender people (TG), based on international standards and disproportionate impact of HIV on these communities. Globally, 43% of new HIV infections in 2019 are estimated to have been among these populations and a further 19% to be among their sexual partners despite key populations making up a much smaller proportion of the total population. Consequentially, HIV prevalence rates among members of these groups are also much higher. Yet HIV treatment outcomes and services consistently lag behind services delivered to other populations.
To end HIV as a global public health threat, tackling the inequities that disproportionately affect key populations is not optional. Improving access to testing, prevention, treatment and other services for key populations, however, can only happen if funding and policy decisions are aligned to address these needs and based on high quality data. Major funders of the global HIV response, including the President's Emergency Plan for AIDS Relief (PEPFAR) and the Global Fund to Fight AIDS, Tuberculosis, and Malaria (Global Fund or GF) have long emphasized the importance of programming targeting key populations, but dynamics of these programs - who is being funded, what work they are funded to do, how communities are consulted and participate, what data are driving the decisions, and the relative size of the funding compared to other investments - is challenging to both access and assess. This dashboard brings together data related to the HIV epidemic, the epidemiology of HIV among key populations, the programmatic response for key populations, and the current policies in place that either facilitate or harm the programmatic response to service delivery for members of key populations.
This table shows the most recent size estimate available from three sources: 1) PEPFAR's Strategic Direction Summary (SDS) for the country; 2) Global Fund denominator data from program reporting for national level results; and 3) UNAIDS KP Atlas (excluding subnational size estimates). For each, the size estimate is compared against the total population to calculate a proportion of the relevant population that is estimated to be part of that key population. The purpose of this table is to show the data that policy makers are using to drive their funding and programming decisions, not to endorse these estimates. In many cases, these estimates are far too low to be relied upon for such decisions.
Population size estimates for key populations are estimates of the number of people in an area - usually a country - that are or identify as members of a key population. Numerous methodologies have been developed and implemented to help researchers and public health experts develop these estimates. These methodologies are frequently implemented through Integrated Bio-Behavioral Surveillance (IBBS) studies in which a range of data on different populations such as frequency of condom use, HIV knowledge and awareness, HIV status, and other characteristics are gathered.
However, population size estimates for key populations are notoriously inaccurate and challenging to assess. Criminalization and stigmatization of key populations create barriers for researchers in gathering a full understanding of how many people are part of an individual key population group. This leads to highly inconsistent estimates, significant intra-regional differences, and incompatible results. Particularly for MSM, homosexuality and bisexuality are innate characteristics with no discernable biological bases for significant regional differentiation. Because of this, the WHO and UNAIDS have recommended minimum thresholds of 1% of the male population between the ages of 15 and 49 be used for programming purposes in areas without high quality alternative estimates available.
From a programmatic side, size estimates are important because they are used by policy makers to determine the flow of resources, develop programmatic responses, and focus programming on populations most at risk. Inaccurate and low size estimates lead decision makers to under-prioritize the programmatic response and underfund service delivery for key populations' specific HIV prevention and treatment needs.
This chart shows all the population size estimates that have been published or used for programmatic decision making from three sources: PEPFAR Strategic Direction Summaries (SDS) since 2014; Global Fund Key Populations Progress Update data; and UNAIDS' Key Population Atlas. The most recent size estimate from each source is highlighted while older size estimates are in grey. To enable comparisons across countries, each size estimate is divided by the total population of the relevant sex between the ages of 15-49 in the year the size estimate was reported. Visualizing these size estimates is NOT endorsement of their accuracy. This chart is meant to enable comparison of a country's size estimates over time and to compare against other countries globally and regionally. In many cases, the range of different size estimates in a region/country demonstrate the challenge of utilizing these data for program and budget planning as different size estimates vary so greatly they can provide very little confidence about the service delivery needs of the population.
This chart shows the most recent HIV prevalence estimate being used in policy decision-making. Where there are multiple HIV prevalence reports available, the most recent estimate reported as being used is shown. As with size estimates above, these data come from three sources: PEPFAR SDSs; Global Fund Progress Update Data; and UNAIDS' Key Population Atlas.
This chart shows funding from both PEPFAR and the Global Fund for each key population. PEPFAR data are based on PEPFAR expenditure or budget reports for each year. Where both are available, the expenditure reporting is utilized. Global Fund data are based on budget data since 2018, and thus don't necessarily represent actual expenditure of funds if there were delays or changes to implementation. The purpose of this chart is to give a more comprehensive picture of the total resources available for KP programming in the country.
PEPFAR's key population program expenditures frequently do not disaggregate by which key population was being targeted. As a result, it is often challenging to understand how PEPFAR is allocating funding to each of these populations. Additionally, this chart includes funding for people in prisons and other enclosed settings (PIP) as a key population. This is to enable cross-comparison between years and funding since the "not disaggregated" funding levels may be inclusive of funding for services targeting PIP.
Detailed specifics of the types of programming that funders are supporting for key populations work is critical to understand how they are viewing the service needs of key populations. Since 2018, PEPFAR has implemented a new financial classification system for tracking expenditures for their programs. As of FY2020, PEPFAR expanded the use of the financial classification system to also include budgets. The financial classification system is highly detailed which enables understanding both the types of programs that are being implemented (program areas and sub-program areas) as well as the targeted populations for each of these programs. Because data are now available for both budgets and expenditures, it is also possible to assess whether expenditures during implementation matched what was originally budgeted. Underspending of KP resources may occur for a number of reasons including delays in the release of funds, programming not being implemented, or program changes. When underspending of resources occurs, they may remain available to be spent in future years on KP programs or they can ultimately be re-directed to support other areas of work either with the original implementing partner or not. If underspending is extensive, it may also lead to PEPFAR decreasing new funding budgeted for KP programs in future years. In places where there is significant underspending, questions should be asked of PEPFAR and the implementing partners as to reasons for underspending and demands made about services being delivered in line with expectations in the budget.
For the Global Fund, far less specific detail is available on either the budget or expenditure side. The Global Fund budgets according to "modules", four of which relate to key populations: 1) Comprehensive prevention programs for MSM; 2) Comprehensive prevention programs for PWID and their partners; 3) Comprehensive prevention programs for sex workers and their clients; and 4) Comprehensive prevention programs for transgender people. Key population programming may occur under other budgeted line items, but it cannot be disaggregated in publicly accessible data. On expenditures, the Global Fund only releases total expenditures incurred on a grant, but not by any line-items or modules. As such, it's not possible to determine whether the key populations specific programming that was budgeted for was actually implemented at the level originally intended.
For both PEPFAR and the Global Fund, the table below will also show what proportion of total funding from each is allocated toward key population programming and how that compares to global and regional program budgets/expenditures.
Select Financial Year:
Budget | Expenditures | Percent Spent |
Select Financial Year:
The network graph to the left shows all implementing partners that are identifiably allocated resources for KP specific programming and/or assigned targets for KP service delivery by PEPFAR. These data are sourced from PEPFAR's Country and Regional Operational Plans, PEPFAR's public datasets, and data from USASpending.gov.
Each circle represents an organization, those in blue are funded directly by PEPFAR while those in red are sub-recipients. The size of each circle is relative to the total funding received. Subrecipient information is only available on grants through USAID, CDC, and U.S. Department of State. Because of the different source, subrecipient funding may come from both PEPFAR and non-PEPFAR sources, as such, specifically comparing the prime partner's total PEPFAR funding against the subrecipient's funding may be inappropriate in some cases.
Hovering over a circle will update information about the individual organization and their network of funders/subrecipients in the table below. Clicking on a circle will lock the focus until a new circle is selected.
A summary table of these relationships with out the specific grant details is available in the downloadable factsheets.