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Programmatic mapping (PM) is a rapid and efficient mechanism to develop size estimates of key populations including female sex workers (FSWs) and geolocate them at physical locations in a systematic and scientific manner. At the macro level, this information forms the basis for allocating program resources, setting performance targets, and assess coverage. At a micro level, PM data provide specific information on hot spots, estimates of FSWs at those spots, and hot spot typology and days and times of operation, all of which provides targeted service delivery strategies. This information can provide a reliable platform to plan HIV prevention and treatment services to considerable scale and intensity. Above all, the entire PM process requires deep involvement of FSWs, which increases community ownership of the data and can lead to an increased uptake of services. Despite a few limitations, the approach is versatile and can be used in varied country contexts to generate important information about sex work and its dynamics. In this paper, we describe experiences and lessons learned from using evidence generated from PM of FSWs in multiple countries to develop HIV prevention programs at scale.
Female sex workers (FSWs) are disproportionately affected by the HIV epidemic [
Acknowledging local epidemic diversity, the Joint United Nations Programme on HIV/AIDS (UNAIDS) Practical Guidelines for Intensifying HIV Prevention recommend the use of local data to inform programs [
More recently, The Global Fund, the World Bank, World Health Organization (WHO) and UNAIDS, as well as various national programs have successfully used programmatic mapping (PM) approaches to estimate size, geo-distribution, operational typologies, and structural determinants of various key populations (KPs) [
The knowledge derived from PM has been used abundantly to provide a reliable platform to plan preventive and treatment services for FSWs. In this paper, we describe experiences and lessons learned from using evidence generated from PM of female sex workers in multiple countries to develop HIV prevention programs for effective coverage at scale.
PM [
During PM fieldwork, the study area is segmented into zones, and an exhaustive list of locations where FSWs congregate is systematically compiled within each zone. Subsequently, these spots are visited with the assistance of local community members (FSWs) to confirm onsite risk activities and the number of FSWs at each location. Population size is estimated at the site level, which is then adjusted to account for double counting and/or mobility across sites, to finally reach an estimated number of FSWs in the study area. Planning for and calculating coverage requires an understanding of where sex work happens and an estimate of various subtypes in each of these locations and their characteristics. One of the key strengths of this approach lies not only in its development of size estimates but also in providing a distribution of FSWs at different hot spots. For planning services and subsequently monitoring coverage, this approach has been proven valuable in ensuring high level coverage [
PM includes 3 main approaches: basic geographic mapping (GM), the Priorities for Local AIDS Control Efforts (PLACE) method, and progressive mapping. Selecting the best approach depends on the context and the availability of time and resources. However, all adhere to the principles of generating location and population size information to design and implement programs, and community ownership and leadership. Although basic GM has been used primarily for mapping and estimating size of KPs, PLACE has been used pragmatically to identify locations where persons meet new partners, and thus, networks where HIV transmission is most likely to occur. Both GM and PLACE have been used where mapping and size estimates are not available and/or more rigorous baseline or follow-up estimates of program coverage are required. Progressive mapping approach is implemented as a component of a more mature program, where it is used quickly by program teams to generate information to scale up programs. A practical difference between the methods is that GM and PLACE include systematic interviews with key informants across all study zones to develop an exhaustive list of sites, whereas progressive mapping uses a crude list of sites from previous mapping as the starting point, available program data, and discussions with peer educators and outreach workers. Each method includes visits to identified spots to verify they are operational, describe their characteristics, and collect information on estimates, typology, and other operational characteristics of the hot spot. This is done by interviewing a key informant, preferably an FSW who operates from the identified spot, or someone knowledgeable about the spot (eg, a bar manager). Both GM and PLACE have extended the value of basic PM by using the venue list as a sampling frame for venue-based biobehavioral surveillance. Examples have been provided in subsequent sections on how countries with large FSW populations such as India, Kenya, and Haiti have used these approaches to gather sufficient information in a timely manner with enough geographic specificity and at low cost to plan KP program scale-up [
Development partners (eg, The Global Fund, the World Bank, the Bill and Melinda Gates Foundation, WHO/UNAIDS, and PEPFAR) have supported various PM approaches in a number of countries.
Countries where various forms of programmatic mapping have been implemented.
There are a number of ways PM data can be used to develop strategic plans for targeted HIV prevention among KPs including FSWs and rapidly establish appropriate programs and basic services. In addition, PM has been used extensively to estimate the size of FSW populations, identify prevention coverage gaps, and quickly institute services where they are nonexistent. The following section presents some examples of how PM data have been used in various countries to strategize, develop, and implement FSW programs.
Conceptually, high impact programs aim to reach the highest number of FSWs with quality services. At the macro level, national and subnational programming [
PM data in Kenya estimated 103,298 FSWs in 7 provinces [
Micro planning decentralizes outreach management and planning to a grass-root level of outreach workers (ORW) and peer educators (PEs) through a process that collects and uses data at an individual level to empower a community to make healthy decisions for themselves [
Through PM, a list of all locations or hot spots where FSWs operate is developed, assigning a range of estimates for FSWs at each spot by subtypology (eg, street, venue, and public place). Furthermore, PM data characterize the spots by providing information on timing of sex work activity at the spot (busiest time of the day or busiest day of the week), which is used as the basis for micro planning. Steps in micro planning include “hot spot validation” identified by PM, followed by “spot load mapping” where FSWs’ peers validate and record peak times and days of operation along with other characteristics of the spot. This is done to build ownership of the PM data by the peers, update spot lists, and estimate the number of PEs required. “Contact mapping” is then done to understand FSW networks and select PEs and determine their allocation across the target area, taking spot clustering in account. “Peer plans” are developed by PEs for each allocated FSW based on her risk and vulnerability, prioritizing those with higher risk and vulnerability. Finally, “Peer calendars” are used to document services provided to each FSW based on individual peer plans and track them at each visit outreach and micro planning [
Likewise, in Mombasa, Kenya, PM data supported successful scale-up of HIV programs for FSWs. PM identified 9208 FSWs with the highest concentration (5809) in Kisauni and Mvita [
PM has been used extensively in a number of countries to produce size estimates of sex worker populations [
Finally, PM data provides service delivery programs with denominators, which are crucial to be able to set goals and establish benchmarks for key outcomes indicators. Key indicators related to program coverage and utilization of programs and services by target populations serve as markers for program success. Coverage gaps at spot level can be evaluated through mapping of these spots on a continuous basis. PM data provide denominators for monitoring 90-90-90 targets and service uptake indicators across the HIV prevention, care, and treatment cascade among FSWs. In Kenya, the national program routinely uses PM data as a denominator to measure the KP program performance every quarter [
Likewise, Pakistan has extensively used PM data to sample KPs for IBBS. In each city, the IBBS sample was distributed based on weights derived from the respective number of KPs in each zone. Spots were randomly selected from spot lists generated by PM within each zone, and later, respondents were selected based on sampling weights assigned to each spot based on spot size, making the sample representative of the overall population [
Information available through programmatic mapping and its use for service delivery planning.
Information | How this information is used |
National size estimates | Develop national strategic plans for HIV prevention, care, and support for key populations |
Decide on national budgetary and resource allocations and costing exercises | |
Set denominators for coverage targets for HIV prevention and treatment programs | |
Evaluate prevention response at a national level and identify coverage gaps | |
Subnational size estimates | Help the country to decide where to prioritize programs to improve meaningful coverage |
Decide on resource allocations at a regional or subnational level | |
Compare prevention response among regions and identify prevention gaps | |
Draw representative samples for key population research by assigning sampling weights based on national distribution of study population | |
Geo-distribution of spots | Target locations/spots for localizing interventions |
Develop local maps and set a plan for coverage | |
Prepare spot clusters and allocate spots to peer educators based on geo-proximity of spots | |
Establish locations for health clinics, drop-in centers, HIV testing centers etc, as well as condom and lubricant distribution channels | |
Number and size of spots | Target locations/spots for localizing interventions |
Decide which spots to prioritize and focus to match coverage targets | |
Operational dynamics of a spot; peak days and peak times of operations | Determine human resource needs, that is, how many peer educators and outreach workers are needed to adequately cover the population. For example, 1 peer educator could work with 50-60 FSWsa, whereas 1 outreach worker can manage working with 5-6 peer educators. |
Size estimates provided at the spot level can be used to estimate the specific number of condoms, lube, outreach testing supplies, and other materials needed | |
The human resource and commodity plan needs to be based on peak estimates so that no one remains uncovered | |
Peak times and peak days might be utilized to determine time of outreach | |
Operational typology of spots/FSWs | Inform intervention design based on the subtypology of spots and FSWs (eg, brothel, street, bar, night club, massage parlor based, and home-based FSWs). |
Use in research | Mapping data is used as a sampling frame for national level surveys, including integrated bio-behavioral surveys. |
aFSWs: female sex workers.
PM is a low-cost and reliable approach designed to generate the most critical information required for planning and implementing effective HIV prevention, care, and treatment programs. PM data have been used at national, provincial, district, subdistrict, and spot levels. At a national level, PM informs funding requirements and resource allocation, program scale-up, target setting, and coverage assessment. At a subnational level, PM prioritizes geographies where interventions should be scaled up to ensure the highest coverage possible within the available resources. Saturating coverage of KPs in high concentration geographies is preferable to spreading services thinly across a wider area. At the district or town level, PM assists programs to assess resources required for outreach and clinical staffs and for commodity requirements such as number of condoms/lube and HIV testing kits. At a spot level, PM enhances outreach to ensure the right number of peer ORWs are available to saturate coverage as well as allocate spots to the most ideal PE. PM further improves program design by carefully evaluating typologies and functional timings of the spots and establishes denominator to monitor access to services and coverage at each spot.
Despite a few limitations, PM provides essential information about the size, distribution, and characteristics of FSWs in a systematic and scientific manner. Above all, the process relies substantially on the strength and involvement of civil society and community organizations that represent and are engaged with KPs. This practically increases the appropriateness and ownership of program design and implementation and results in increased uptake and more efficient and effective programs based on the needs and priorities of the FSW community.
female sex workers
geographic mapping
integrated bio-behavioral survey
key populations
outreach worker
peer educator
Priorities for Local AIDS Control Efforts
programmatic mapping
Joint United Nations Programme on HIV/AIDS
World Health Organization
The authors would like to acknowledge research teams in all countries where PM was conducted. They would like to thank the Ministries of Health in several counties where PM has been conducted in partnership. They thank international donors, that is, The World Bank, Bill and Melinda Gates Foundation, and GFATM for their funding support to conduct PM in various countries. This publication was made possible by the generous support of the American people through the United States Agency for International Development and the United States President’s Emergency Plan for AIDS Relief (PEPFAR) through the LINKAGES project, cooperative agreement number AID-OAA-A-14-00045. The contents of this publication are the sole responsibility of LINKAGES and do not necessarily reflect the views of USAID, PEPFAR, or the US Government.
FE conceptualized the whole paper, developed the first draft, and finalized the manuscript. SSW, NP, and PB wrote programmatic examples and provided additions in the discussion section. SI wrote up a large part of the conclusion section and added examples in the text.
None declared.