Population Size Estimation of Men Who Have Sex with Men in Tbilisi, Georgia; Multiple Methods and Triangulation of Findings

Sulaberidze, Lela; Mirzazadeh, Ali; Chikovani, Ivdity; Shengelia, Natia; Tsereteli, Nino

doi:10.1371/journal.pone.0147413

Cited by 27 publications

(31 citation statements)

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“…This finding should be interpreted with caution given the subjectiveness of the method and its succeptibility to several biases and unmeasured influences which may lead to under- or over- estimations. Indeed, previous studies applying multiple PSE methods including WOTC, the WOTC method have shown both under-estimation (e.g., MSM in Nairobi in Kenya, FSW in Yangon and Mandalay in Myanmar [ 14 , 25 ]), or over-estimation (e.g., MSM in Georgia [ 9 ]) of the population size in compare with other size estimation methods. Considering the highly criminalized and stigmatised nature of sex work in Iran [ 6 ], FSW might have exaggerated the estimates in an effort to normalize their sex work practice.…”

Section: Discussionmentioning

confidence: 99%

“…We also integrated the service and unique object multiplier methods [ 3 , 9 ] into the 2015 IBBS surveys to estimate the number of FSW in the 13 cities. Estimation of the total size of the population using multiplier methods relies on two overlapping but independent sources of information.…”

Section: Methodsmentioning

confidence: 99%

“…Given the absence of a single gold standard or bias-free approach, we adapted and applied several methods, namely wisdom of the crowds (WOTC) [ 7 , 8 ], service and unique object multipliers [ 1 , 3 , 9 ], and network scale-up (NSU) [ 10 , 11 ]), to estimate the population size of FSW in Iran. We synthesized the findings of these several approaches to arrive at a more robust estimate to better inform health policies and guide research to improve the health of FSW in Iran.…”

Section: Introductionmentioning

confidence: 99%

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Population size estimation of female sex workers in Iran: Synthesis of methods and results

et al. 2017

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IntroductionEstimating the number of key populations at risk of HIV is essential for planning, monitoring, and evaluating prevention, care, and treatment programmes. We conducted this study to estimate the number of female sex workers (FSW) in major cities of Iran.MethodsWe used three population size estimation methods (i.e., wisdom of the crowds, multiplier method, and network scale-up) to calculate the number of FSW in 13 cities in Iran. The wisdom of the crowds and multiplier methods were integrated into a nationwide bio-behavioural surveillance survey in 2015, and the network scale-up method was included in a national survey of the general population in 2014. The median of the three methods was used to calculate the proportion of the adult female population who practice sex work in the 13 cities. These figures were then extrapolated to provide a national population size estimation of FSW across urban areas.ResultsThe population size of FSW was 91,500 (95% Uncertainty Intervals [UIs] 61,400–117,700), corresponding to 1.43% (95% UIs 0.96–1.84) of the adult (i.e., 15–49 year-old) female population living in these 13 cities. The projected numbers of FSW for all 31 provincial capital cities were 130,800 (95% UIs 87,800–168,200) and 228,700 (95% UIs 153,500–294,300) for all urban settings in Iran.ConclusionsUsing methods of comparable rigor, our study provided a data-driven national estimate of the population size of FSW in urban areas of Iran. Our findings provide vital information for enhancing HIV programme planning and lay a foundation for assessing the impact of harm reduction efforts within this marginalized population.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Population size estimation of female sex workers in Iran: Synthesis of methods and results

et al. 2017

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“…FSW and MSM together accounted for 9.3% of Yunnan's estimated prevalent cases in 2017. This is lower than the share of these key groups in past Spectrum-STI estimates 35,36,40 , and in HIV incidence estimates [41][42][43][44] , which reflects that both the estimated prevalence of syphilis in FSW and Yunnan's key population size estimates are lower than in other countries 7,9,45,46 . The size estimate of FSW was based on self-identified sex workers; and almost certainly is an under-estimate of the total number of women who engage in transactional sex work.…”

Section: Discussionmentioning

confidence: 81%

The Spectrum-STI Groups model: syphilis prevalence trends across high-risk and lower-risk populations in Yunnan, China

Korenromp¹,

Zhang

et al. 2020

Sci Rep

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Spectrum-Sti model, structured by subgroups within a population, was used in a workshop in Yunnan, China, to estimate provincial trends in active syphilis in 15 to 49-year-old adults. Syphilis prevalence data from female sex workers (fSW), men who have sex with men (MSM), and lower-risk women and men in Yunnan were identified through literature searches and local experts. Sources included antenatal care clinic screening, blood donor screening, HiV/Sti bio-behavioural surveys, sentinel surveillance, and epidemiology studies. The 2017 provincial syphilis prevalence estimates were 0.26% (95% confidence interval 0.17-0.34%) in women and 0.28% (0.20-0.36%) in men. Estimated prevalence was 6.8-fold higher in FSW (1.69% (0.68-3.97%) than in lower-risk women (0.25% (0.18-0.35%)), and 22.7-fold higher in MSM (5.35% (2.74-12.47%) than in lower-risk men (0.24% (0.17-0.31%). For all populations, the 2017 estimates were below the 2005 estimates, but differences were not significant. In 2017 FSW and MSM together accounted for 9.3% of prevalent cases. These estimates suggest Yunnan's Sti programs have kept the overall prevalence of syphilis low, but prevalence remains high in FSW and MSM. Strengthening efforts targeting FSW and MSM, and identification of other risk populations e.g. among heterosexual men, are critical to reduce syphilis. Spectrum-STI is a statistical trend-fitting model designed for countries to estimate trends over time in the prevalence and incidence of three sexually transmitted infections (STIs): syphilis (etiologic agent: Treponema pallidum subspecies pallidum); gonorrhea (Neisseria gonorrhoeae); and chlamydia (Chlamydia trachomatis) from available prevalence data after standardizing for diagnostic test, location and age and weighted to reflect representativeness. The model builds on the Spectrum suite of health policy planning and surveillance models developed by Avenir Health 1. The latest version of Spectrum-STI, the Spectrum-STI Groups model, allows for estimates to be generated for different higher-risk and lower-risk groups in a population and for these to be combined to form an overall population estimate. In November 2018, Spectrum-STI Groups was piloted in a 3-day workshop held in Kunming, Yunnan's capital, organized by the Yunnan provincial Center for Disease Control and Prevention (CDC) and the World Health Organization (WHO). Yunnan province is located in the southwest of China and in 2017 had a population of just under 46 million (3.4% of China's population). It is one of three provinces chosen by China's National Health and Family Commission and UNICEF to pilot validating elimination of mother-to-child transmission of HIV, syphilis and

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“…Inference is made based on rearranging the simple identity p t = M t / N to solve for N . Although the multiplier method is only defined for a single trait, in recent applications, one sees a trend in using data on multiple traits to infer the size of the same population (Sulaberidze et al ; Johnston et al ; Okal et al ; Raymond et al ) in hopes of “strength in numbers.” Often this happens when the marginal counts for several traits are already available to a public health agency, so that resources are spent only to gather data on trait proportions within the target population via a single sample survey. In the cited studies, this collection of data is analysed on a trait‐by‐trait basis without aggregating the information into one single estimate; hence, we cannot be certain of the amount of information truly gained.…”

Section: Introductionmentioning

confidence: 99%

Inferring population size: extending the multiplier method to incorporate multiple traits with a likelihood‐based approach

Meng

Gustafson

2016

Stat

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Estimating population size is an important task for resource planning and policy making. One method is the "multiplier method" that uses information about a binary trait to infer the size of a population. This paper presents a likelihood-based estimator that generalizes the multiplier method to accommodate multiple traits as well as any number of categories in a trait. To provide guidelines for study design, we quantify the advantage of using multiple traits (multiple multipliers) by studying the estimator's asymptotic standard deviation (ASD). Inclusion of multiple traits reduces the ASD most effectively when the traits are uncorrelated and of low prevalence (roughly less than 10%), but the amount of reduction in ASD diminishes when the number of traits becomes large. A Bayesian implementation of our method is applied to both simulated data and real data pertaining to an injection-drug user population.marginal counts can only increase with increasing traits when these counts are given by past records. It is clear that, foremost, we require a method capable of combining data on multiple traits to form a single estimate, then, upon analysing this method, understand how to benefit from using a reasonable number of traits.In this paper, a method for analysing multiple trait multiplier data is presented based on a "reference" likelihood under the assumption of independent and identically distributed (i.i.d.) survey sampling in a large population. By using an i.i.d. likelihood as a reference, a simple Fisher information matrix is available to us for exploring the association between information gain and properties of a collection of traits. One strategy to extend to non-i.i.d sampling is to use the outlined likelihood as an invariant core and to make additional adjustments to reflect a particular survey design. This technique is outlined in a demonstrative application to estimate the size of the injection-drug user (IDU) population in San Francisco in 2009 with data given by Johnston et al. (2013). The paper closes with an investigation on how estimation error is influenced by the number and type of traits that is included in the study.

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Population Size Estimation of Men Who Have Sex with Men in Tbilisi, Georgia; Multiple Methods and Triangulation of Findings

Cited by 27 publications

References 22 publications

Population size estimation of female sex workers in Iran: Synthesis of methods and results

Population size estimation of female sex workers in Iran: Synthesis of methods and results

The Spectrum-STI Groups model: syphilis prevalence trends across high-risk and lower-risk populations in Yunnan, China

Inferring population size: extending the multiplier method to incorporate multiple traits with a likelihood‐based approach

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