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dc.contributor.authorCheuk, Eve
dc.contributor.authorIsac, Shajy
dc.contributor.authorMusyoki, Helgar K
dc.contributor.authorPickles, Michael
dc.contributor.authorBhattacharjee, Parinita
dc.contributor.authorGichangi, Peter
dc.contributor.authorLorway, Robert R
dc.contributor.authorMishra, Sharmistha
dc.contributor.authorBlanchard, James F
dc.date.accessioned2021-05-11T08:09:02Z
dc.date.available2021-05-11T08:09:02Z
dc.date.issued2016
dc.identifier.urihttps://ir.tum.ac.ke/handle/123456789/17358
dc.description.abstractBackground: Standard programmatic mapping involves identifying locations where key populations meet, profiling of these locations (hotspots) and estimating the key population size. Information gained from this method has been used for HIV programming – resource allocation, program planning, service delivery, and monitoring and evaluation – for people who inject drugs, men who has sex with men, and female sex workers (FSW). With an increasing focus on adolescent girls and young women (AGYW) as a priority population for HIV prevention, programs need to know where and how to effectively reach individuals that are at increased risk for HIV but were conventionally considered part of the general population. We hypothesize that AGYW who engage in transactional and casual sex also congregate at sex work hotspots to meet sex partners. Therefore, we adapted the standard programmatic mapping approach to understand the geographic distribution and population size of AGYW in Mombasa County, Kenya. Objectives: The objectives are several-fold: (1) to detail and compare the modified programmatic mapping approach used in this study to the standard approach; (2) to estimate the number of young FSW; (3) to estimate the number of AGYW who congregate in sex work hotspots to meet sex partners other than clients; (4) to estimate the overlap in sexual network in hotspots; (5) to describe the distribution of sex work hotspots across Mombasa and its four sub-counties; and (6) to compare the distribution of hotspots that were known to the local HIV prevention program prior to this study and those newly identified. Methods: The standard programmatic mapping approach was modified to estimate the population of young women aged 14-24 years who visit sex work hotspots in Mombasa to meet partners for commercial, transactional and casual sex. Results: We estimated that there were 11,777 FSW (range 9,265-14,290) in Mombasa in 2014; among whom, 6,127 (52.0%) were 14-24 years old. The population estimate for women aged 14- 24 years who engaged in transactional and casual sex and congregated at the hotspots were 5,348 (range 4,185-6,510) and 4,160 (range 3,194-5,125), respectively. Of the 1,025 validated sex work hotspots, 856 (83.5%) were locations also visited by women engaged in both transactional and casual sex. Only 48 (4.7%) hotspots were exclusive sex work locations. The geographic and typological distribution of hotspots were significantly different between the four sub-counties (P < .001). Of the 1,025 hotspots, 419 (40.9%) were already known to the local HIV prevention program and 606 (59.1%) were newly identified.Conclusions: Using the adapted programmatic mapping approach detailed in this study, our results show that HIV prevention programs tailored to AGYW can focus delivery of their interventions to traditional sex work hotspots to reach subgroups that may be at increased risk for HIV.en_US
dc.language.isoenen_US
dc.subjectprogrammatic mappingen_US
dc.subjectkey population size estimationen_US
dc.subjectfemale sex workersen_US
dc.subjectadolescent girls and young womenen_US
dc.subjectsex worken_US
dc.subjecttransactional sexen_US
dc.subjectcasual sexen_US
dc.subjectHIV preventionen_US
dc.titleAdapting methods of key population programmatic mapping and enumeration to inform HIV prevention programs for adolescent girls and young womenen_US
dc.typeArticleen_US


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