Capture-Recapture Among Men Who Have Sex With Men and Among Female Sex Workers in 11 Towns in Uganda

Abstract

Background Key populations at higher risk for HIV infection, including people who inject drugs, men who have sex with men (MSM), and female sex workers (FSWs), are disproportionately affected by the HIV/AIDS epidemic. Empirical estimates of their population sizes are necessary for HIV program planning and monitoring. Such estimates, however, are lacking for most of Uganda’s urban centers. Objective The aim of this study was to estimate the number of FSWs and MSM in select locations in Uganda. Methods We utilized conventional 2-source capture-recapture (CRC) to estimate the population of FSWs in Mbale, Jinja, Wakiso, Mbarara, Gulu, Kabarole, Busia, Tororo, Masaka, and Kabale and the population of MSM in Mbale, Jinja, Wakiso, Mbarara, Gulu, Kabarole, and Mukono from June to August 2017. Hand mirrors and key chains were distributed to FSWs and MSM, respectively, by peers during capture 1. A week later, different FSWs and MSM distributors went to the same towns to collect data for the second capture. Population size estimates and 95% CIs were calculated using the CRC Simple Interactive Statistical Analysis. Results We estimated the population of FSWs and MSM using 2 different recapture definitions: those who could present the object or identify the object from a set of photos. The most credible (closer to global estimates of MSM; 3%-5%) estimates came from those who presented the objects only. The FSW population in Mbale was estimated to be 693 (95% CI 474-912). For Jinja, Mukono, Busia, and Tororo, we estimated the number of FSWs to be 802 (95% CI 534-1069), 322 (95% CI 300-343), 961 (95% CI 592-1330), and 2872 (95% CI 0-6005), respectively. For Masaka, Mbarara, Kabale, and Wakiso, we estimated the FSWs population to be 512 (95% CI 384-639), 1904 (95% CI 1058-2749), 377 (95% CI 247-506), and 828 (95% CI 502-1152), respectively. For Kabarole and Gulu, we estimated the FSWs population to be 397 (95% CI 325-469) and 1425 (95% CI 893-1958), respectively. MSM estimates were 381 (95% CI 299-462) for Mbale, 1100 (95% CI 351-1849) for Jinja, 368 (95% CI 281-455) for Wakiso, 322 (95% CI 253-390) for Mbarara, 180 (95% CI 170-189) for Gulu, 335 (95% CI 258-412) for Kabarole, and 264 (95% CI 228-301) for Mukono. Conclusions The CRC activity was one of the first to be carried out in Uganda to obtain small town–level population sizes for FSWs and MSM. We found that it is feasible to use FSW and MSM peers for this activity, but proper training and standardized data collection tools are essential to minimize bias.

Methods for Estimating Population Size for Key Populations: A Global Scoping Review for HIV Research

“…In order to prevent the collection of personal identi cation information, unique objects such as coupons are commonly used to identify recaptures. However, calculating the number of recaptures is challenging because the databases used may not record the same unique objects from individuals (13). In some cases, there is no way to determine if the person with the unique object in the second capture is the same person who received it in the rst capture (27).…”

Prevalence and Factors Associated with Major Depression Among Female Sex Workers in Post-Conflict Gulu District: A Cross-Sectional Study

“…More than 80% of the inhabitants of the district practice subsistence farming (20). Gulu district has an estimated 1425 FSWs (21), majority of whom work and live within Gulu municipality. Unpublished program data show that more than 1300 fully mapped-out FSWs receive either HIV treatment or HIV preventive services from TASO Gulu.…”

Evolving HIV epidemics

“…Multiplier methods can underestimate numbers if key population program data are limited or populations are unrecognized and/or inaccessible to surveyors, for example, when stigmatized population members misreport their risk. These issues have been observed in size estimation estimates in the region for both MSM and sex workers [49,50]. Serious efforts to improve size estimates have often used multiple methods [51–53] or applied innovative approaches, for example, Bayesian techniques applied to RDS multipliers [54] or combining venue-based sampling and RDS [55].…”