Female sex workers population size estimation in Rwanda using a three-source capture−recapture method

Musengimana, Gentille; Tuyishime, Elysee; Remera, Eric; Dong, Maxia; Sebuhoro, Dieudonné; Mulindabigwi, Augustin; Kayirangwa, Eugenie; Malamba, Samuel; Gutreuter, Steve; Prybylski, Dimitri; Doshi, Reena H.; Kayitesi, Catherine; Mutarabayire, V.; Nsanzimana, Sabin; Mugwaneza, Placidie

doi:10.1017/s0950268821000595

Cited by 7 publications

(12 citation statements)

References 10 publications

(19 reference statements)

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“…PSE based on the method known by the monikers "capture-recapture" and the "multiplier method" is a statistically principled approach which has been widely used to estimate the sizes of KPs [10][11][12][13][14][15][16][17][18][19][20]. Such multiple-list PSE is commonly based on only two lists, but three-or-more-list estimation [21][22][23][24] is becoming increasingly common.…”

Section: Introductionmentioning

confidence: 99%

Comparative performance of multiple-list estimators of key population size

Gutreuter

2022

PLOS Glob Public Health

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Estimates of the sizes of key populations (KPs) affected by HIV, including men who have sex with men, female sex workers and people who inject drugs, are required for targeting epidemic control efforts where they are most needed. Unfortunately, different estimators often produce discrepant results, and an objective basis for choice is lacking. This simulation study provides the first comparison of information-theoretic selection of loglinear models (LLM-AIC), Bayesian model averaging of loglinear models (LLM-BMA) and Bayesian nonparametric latent-class modeling (BLCM) for estimation of population size from multiple lists. Four hundred random samples from populations of size 1,000, 10,000 and 20,000, each including five encounter opportunities, were independently simulated using each of 30 data-generating models obtained from combinations of six patterns of variation in encounter probabilities and five expected per-list encounter probabilities, producing a total of 36,000 samples. Population size was estimated for each combination of sample and sequentially cumulative sets of 2–5 lists using LLM-AIC, LLM-BMA and BLCM. LLM-BMA and BLCM were quite robust and performed comparably in terms of root mean-squared error and bias, and outperformed LLM-AIC. All estimation methods produced uncertainty intervals which failed to achieve the nominal coverage, but LLM-BMA, as implemented in the dga R package produced the best balance of accuracy and interval coverage. The results also indicate that two-list estimation is unnecessarily vulnerable, and it is better to estimate the sizes of KPs based on at least three lists.

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Section: Introductionmentioning

confidence: 99%

Comparative performance of multiple-list estimators of key population size

Gutreuter

2022

PLOS Glob Public Health

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“…This study represents the first implementation of these sampling and analytic methods to produce large-scale population size estimates for female sex workers, men who have sex with men, and people who inject drugs in Nigeria. Several other applications of 3S-CRC and Bayesian nonparametric latent-class models to estimate female sex worker population sizes in sub-Saharan Africa have been published recently, in South Sudan [ 20 ], Kampala, Uganda [ 21 ], and Rwanda [ 22 ], but to our knowledge no other studies have used these sampling and analytic methods for men who have sex with men or people who inject drugs. Although we were unable to define each hotspot as either urban or rural, and all local government areas thus included urban and rural areas, our study included every local government area in each of the 7 states, and thus represents broad coverage.…”

Section: Discussionmentioning

confidence: 99%

“…These examples of successful population size estimates using 3S-CRC data were analyzed using Bayesian nonparametric latent-class models [23]. We expanded use of 3S-CRC sampling of key populations from female sex workers in East Africa [20][21][22] to female sex workers, men who have sex with men, and people who inject drugs in Nigeria.…”

Section: Introductionmentioning

confidence: 99%

“…In 2009, 2-source capture-recapture was used to estimate the population size of men who have sex with men in 3 large Nigerian cities [ 19 ]. Since these efforts, improved methods like 3-source capture-recapture (3S-CRC) sampling have been used to estimate population sizes of female sex workers in sub-Saharan African countries, such as South Sudan [ 20 ], Uganda [ 21 ], and Rwanda [ 22 ]. Compared to programmatic mapping and enumeration, which incorporate only those populations present and visible at a venue, the 3S-CRC sampling approach is an improvement, because it accounts for lack of social visibility, thereby producing more realistic population size estimates to inform HIV prevention and treatment programs for key populations.…”

Section: Introductionmentioning

confidence: 99%

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Key Population Size Estimation to Guide HIV Epidemic Responses in Nigeria: Bayesian Analysis of 3-Source Capture-Recapture Data

McIntyre¹,

Mitchell²,

Stafford³

et al. 2022

JMIR Public Health Surveill

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Background Nigeria has the fourth largest burden of HIV globally. Key populations, including female sex workers, men who have sex with men, and people who inject drugs, are more vulnerable to HIV than the general population due to stigmatized and criminalized behaviors. Reliable key population size estimates are needed to guide HIV epidemic response efforts. Objective The objective of our study was to use empirical methods for sampling and analysis to improve the quality of population size estimates of female sex workers, men who have sex with men, and people who inject drugs in 7 states (Akwa Ibom, Benue, Cross River, Lagos, Nasarawa, Rivers, and the Federal Capital Territory) of Nigeria for program planning and to demonstrate improved statistical estimation methods. Methods From October to December 2018, we used 3-source capture-recapture to produce population size estimates in 7 states in Nigeria. Hotspots were mapped before 3-source capture-recapture started. We sampled female sex workers, men who have sex with men, and people who inject drugs during 3 independent captures about one week apart. During hotspot encounters, key population members were offered inexpensive, memorable objects unique to each capture round. In subsequent rounds, key population members were offered an object and asked to identify objects received during previous rounds (if any). Correct responses were tallied and recorded on tablets. Data were aggregated by key population and state for analysis. Median population size estimates were derived using Bayesian nonparametric latent-class models with 80% highest density intervals. Results Overall, we sampled approximately 310,000 persons at 9015 hotspots during 3 independent captures. Population size estimates for female sex workers ranged from 14,500 to 64,300; population size estimates for men who have sex with men ranged from 3200 to 41,400; and population size estimates for people who inject drugs ranged from 3400 to 30,400. Conclusions This was the first implementation of these 3-source capture-recapture methods in Nigeria. Our population size estimates were larger than previously documented for each key population in all states. The Bayesian models account for factors, such as social visibility, that influence heterogeneous capture probabilities, resulting in more reliable population size estimates. The larger population size estimates suggest a need for programmatic scale-up to reach these populations, which are at highest risk for HIV.

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“…Female sex workers (FSWs) are one of the populations most at risk for becoming infected with HIV in sub-Saharan Africa, a region with the worst disease burden globally. In Rwanda, there are an estimated 15,000 FSWs [ 1 ]. The HIV prevalence among FSWs in Rwanda was estimated to be approximately 46% in 2015.…”

mentioning

confidence: 99%