Bhatta et. al (Accumulation of Biological and Behavioral Data of Female Sex Workers …) 10.26555/eshr.v6i2.9845 Review Article Accumulation of Biological and Behavioral Data of Female Sex Workers Using Respondent-Driven Sampling Around the World: Systematic Review Mihir Bhatta1,*, Agniva Majumdar1, Piyali Ghosh1 , Sitikantha Banerjee2, Debjit Chakraborty1, Subrata Biswas1, Srijan Sahoo1, Shanta Dutta1 1 ICMR-National Institute of Cholera and Enteric Diseases, Kolkata - 700010, India 2 AIIMS, Jammu, Jammu and Kashmir 180001, India * Correspondence: mihirbhatta@gmail.com. Phone: +919051821957 Received 27 Feb 2024; Accepted 01 August 2024; Published 19 Dec 2024 ABSTRACT Background: Respondent-Driven Sampling (RDS) is generally used to study hidden or hard-to-reach populations. The objective of the present work is to describe the initiation, implementation, and complications that arise during RDS of female sex workers (FSWs) around the world. Method: Behavioural and biological data of FSWs collected through RDS was mined from peer-reviewed articles, published during 2010-2022. Review protocol was developed and registered in the PROSPERO (registration number CRD42022346470) and published separately. Results: It was found that most of the RDS (69 articles, globally) were largely successful in the recruitment of FSWs, with varying response rates. Conclusion: Present outcomes supports the application of RDS in surveillance for any such population by providing a minimal set of parameters of testing procedures (methodology) including methods to evaluate the quality also. Keywords: Respondent-driven Sampling (RDS); Female sex workers (FSW); Sampling; RDS implementation; Hidden population; Hard to reach population INTRODUCTION The Respondent-driven Sampling (RDS) method is a non-probability sampling method that approximates probability sample design, allowing for extrapolating results to the target population. Studying communities that are hidden or difficult to reach has certain limits, which are typically addressed by this approach.1 In the early 1990s, the phrase "hard-to-reach population" was coined in the field of public health to describe poor socioeconomic and low literacy populations, ethnic minorities, and those, who are not successfully reached by the health workers through various healthcare initiatives. The phrase "hidden population" was created by social science researchers to refer to the population with an inadequate sampling frame. This may occur either they belong to an unorthodox occupational group (female sex workers) or closed social groups (men who have 87Vol. 6, No. 2, 2024, pp. 87-105 https://doi.org/10.26555/eshr.v3i1.3629 Bhatta et. al (Accumulation of Biological and Behavioral Data of Female Sex Workers …) Vol. 6, No. 2, 2024, pp. 87-105 10.26555/eshr.v6i2.9845 sex with men), or have unsocial behaviours (injecting drug users), or very small population size belong to an ununorthodox occupational group (transgenders), among others.1 RDS was originally developed by Heckathorn2 as a chain-reference sampling method that traces data from one individual to another by relational succession. Stochastic Markov chain modeling, snowball sampling, and the theory of biased networks (homophily model) are all combined in this method1. The idea that every individual, regardless of the size of the network, is indirectly connected to every other individual through around six intermediaries is another notion the authors rely on to explain the "small world" phenomena. In the event that this premise is accurate, any randomly selected individual can be reached in the sixth wave of a reference chain, including the most socially isolated individuals2. Additional sociological theories—particularly behavioral theories—provide additional justifications for the "small world" phenomena. RDS has been used in a number of countries to gather data from populations at higher risk of HIV exposure, including female sex workers (FSW), men sex with men (MSM), injecting drug users (PWUD, PWID), and other individuals deemed “hard-to- reach” because of social stigma and engagement in socially unaccepted behavior.1,3 With the guidance of agencies like the US Centers for Disease Control and Prevention, UNAIDS, the Global Fund, WHO and others, this sampling technique has been used over the years to generate data on the baseline and trend analysis for prevalence estimation, study on risk behaviors, and the impact of the program on HIV and other sexually transmitted infections through biological and behavioral assessments.3 In a range of contexts the sampling technique is proven viability and success in attracting hidden populations of IDUs, resulting in a quick acquired of long and diverse recruitment chains. It has been used in a number of countries to gather biological and behavioral information from male who have sex with male (e.g., Bangladesh, Cambodia, Uganda, United States) and sex workers (e.g., Vietnam, India).3–4 RDS begins with a set number of participants, referred to as "seeds," who are selected from the target population, chosen with care by the surveillance team. Samples are created through peers giving coupons to one another.Each participant receives a limited quantity of coupons, which restricts the excessive contributions made by those with more connections to other members of the same network. These save participants from providing specific details on their recruits, allowing researchers to see the recruitment process in action.5 To guarantee continued involvement and appropriate recruitment, those who are taking part in the survey and enlisting peers are given "incentives." A protracted recruitment chain made up of numerous "waves" of recruits may emerge from this recruitment process. As the recruitment chains lengthen, the sample arrangement becomes less dependent on the purposefully chosen seeds.6 Following sample collection, statistical modifications are made to account for variations in network sizes and recruiting efforts, yielding data on estimates that are representative of the population's network.The fact that most 1-2,5 FSWs are mobile and frequently move between solicitation points, within and to other districts, towns, states, and provinces, which makes them difficult to reach. 7 Some ladies are difficult to locate as they engage in part-time sex work. Higher paid sex workers have the option to stay anonymous, such as those who use apps, the internet, or agencies to solicit. Through bio-behavioural surveillance efforts, FSWs in many countries have also been sampled using a probability sampling technique time location sampling (TLS). TLS, however, can only represent FSWs those are readily recognizable at visible places; as a result, it may omit potentially significant information from other kinds of FSWs. Since there hasn't been much experience with RDS yet, more testing is necessary to confirm this modality. The viability 88 https://doi.org/10.26555/eshr.v3i1.3629 Bhatta et. al (Accumulation of Biological and Behavioral Data of Female Sex Workers …) Vol. 6, No. 2, 2024, pp. 87-105 10.26555/eshr.v6i2.9845 of using this sampling technique to find hidden populations of FSWs in environments where access to FSWs and the organization of sex work are tightly regulated, and where there is minimal or no interaction between the target population and community resources, is not well understood.7 In this context, objective of the present article is to describe implementation and outcome of RDS practices to accumulate biological and behavioral informations of FSW population, around the world. METHOD Details of the methods for the present article is developed as a separate protocol registered in the PROSPERO (registration number CRD42022346470) and published in a peer reviewed journal.8 Eligibility criteria A total of 438 articles and abstracts are initially included after the initial search. Present search is further refined by removing abstracts and texts as duplicated (n = 177), without relevant protocols (n = 49), or claimed but not using RDS (n = 75) and review articles (n = 68). There were several publications found for a particular study and all related articles were reviewed and included on the previously prepared extraction sheet. This brings about 69 articles representing 76 different surveys included in the present work Figure 1, based on WHO classifications of regions.9 Figure 1. Flow digram of RDS extraction Data extraction The data has been extracted from 69 full text (Table 1) published articles10-77 through Epi Info™ (Ver. 6.0) generated modified data extraction tool accordance to the STROBE-RDS 89 https://doi.org/10.26555/eshr.v3i1.3629 Bhatta et. al (Accumulation of Biological and Behavioral Data of Female Sex Workers …) Vol. 6, No. 2, 2024, pp. 87-105 10.26555/eshr.v6i2.9845 (Strengthening the Reporting of Observational Studies in Epidemiology for Respondent- Driven Sampling) guideline. That was arranged into six sub-tables in Table-1 based on WHO classifications of regions:9 African Region (AFR), Region of the Americas (AMR), South-East Asian Region (SEAR), European Region (EUR), Mediterranean Region (EMR), and Western Pacific Region (WPR). The included reviewed indicators whose apprising design and implementation of the survey are observed and subjected to further analysis. Indicators informing survey design and implementation, year of publication, criteria for eligibility, specimen type/s collected for lab testing, pre-survey research was conducted or not, number and position of recruitment sites, methods of interview, the actual number of seeds at the start and at the end (and whether seeds were added or failed during data collection), amount and kind of primary and secondary incentives (in USD), calculated target and final sample size, design effect used in sample size calculation, the duration of data collection (in weeks), maximum number of waves, and maximum number of coupons distributed to each recruiter. Further analysis was carried out to find whether equilibrium or convergence was assessed or not, whether data were adjusted for network size, software used or not, etc. Preparation of map Topographical sheets of world map have been scanned, geo-referenced, and then digitized with the help of quantum geographic information system (Q-GIS), a free, open-sourced, cross- platform desktop-based GIS application, written in C++, Python, QT languages and provides services like viewing, editing, analysis of geospatial data. Data based on the region has been entered to the newly prepared digitized map as the non-spatial data or attributes78. Case definition In the present study, female sex workers are considered as those who are females and born biologically same, and actively engaged in sailing sex in terms of money/ gift or both.79 Data analysis Frequencies were used to describe the studies and their findings. The details of starting year of the study and pre-survey investigation, suitability of age, number of seeds at the beginning and end of the survey, duration of the survey, ultimate sample size, assessed design effect, the span of longest recruitment chain, and adjustment of RDS were reported accordingly. Thematic analysis was performed to identify the outcomes (challenges, reasons, and suggested interventions) common between studies.80-83 The evidence was synthesized manually and the conceptual model was presented in a tabular sheet. RESULTS The available previously published articles on RDS were belongs to the following WHO regions 8: 34 studies from the African Region (AFR), 11 studies from the Region of the Americas (AMR), 11 studies from the South-East Asian Region (SEAR), four from the European Region (EUR), 6 studies from the Eastern Mediterranean Region (EMR) and 9 studies from the Western Pacific Region (WPR) (Figure 2). There were ten articles from India, nine articles from Brazil, six from Zimbabwe, five from China, four articles each from Togo, Swaziland, South Africa, and Papua-New Guinea; three articles each from Sudan and Kenya; two articles each from Uganda, Namibia, Iran, and Burkina Faso. The rest of the included countries had one article from each (Table 1). The key challenges faced by researchers while recruiting FSWs using RDS have been described here in detailed. The challenge reported by most of the studies is the poor response rate,84-86 which was measured in different ways by low coupon return rate and the considerable number of seeds being non-productive. As a result, the workers either did not complete recruiting the desired sample within the stipulated time, had to increase the duration of data 90 https://doi.org/10.26555/eshr.v3i1.3629 Bhatta et. al (Accumulation of Biological and Behavioral Data of Female Sex Workers …) Vol. 6, No. 2, 2024, pp. 87-105 10.26555/eshr.v6i2.9845 collection, or added new seeds when the data collection process was ongoing.79 The key reasons for poor response rate were found to be less mixing/ networking of FSWs and their high level of independence, external control of FSW restricted freedom of movement and perception of inadequate incentive and their mistrust towards researchers due to poor community involvement67. Moreover, accessibility, acceptability, and timing of RDS sites and social stigma also resulted from low coupon returns.80 Pre-surveillance formative research involving community representatives (community representatives are often former or current sex workers themselves, who can understand and address the unique challenges faced by their community) was considered as crucial for assessing network characteristics and feasibility of RDS in the study setting. Other interventions for improving response included intensive rapport building, provision of services along with research, finalization of RDS site, and nature of incentive after discussion with study participants.81 Selection bias could occur due to high homophily, i.e. tendency of participants to recruit others with similar characteristics.82 This could be minimized by weighted analysis and statistical modelling.83 RDS could miss a selected geographical pocket where seeds were non- productive, and their characteristics could be significantly different from those who were selected.84 The use of primary and secondary incentives was likely to attract the FSWs with poor socioeconomic status, but unlikely to involve those with higher purchasing power.85 A meticulous seed selection could decrease such selection bias by recruiting FSWs from different geographical divides, social statuses and occupational differences.84 Research had revealed that known HIV-infected persons could have a high probability of refusing to attend RDS sites and get tested for HIV, compared to their counterparts, as a result, RDS could under-estimate prevalence of HIV.85 On the other hand, inaccurate reporting of network size could result in a biased sampling weight, which could adversely affect the outcome.86 Scientists are suggested that the accuracy of reporting network size could be checked by collecting network size-related data both during the main interview and in the follow-up interview (while collecting secondary incentives), and conducting test-retest reliability of this estimate.87 Among the 69 previously published articles, 64 articles are found to be reported HIV prevalence point estimations above zero, and one article selected was not on HCV instead of HIV. 32 articles (46.37 %) included all three components to facilitate the design of calculated design effect for HIV prevalence. 6 articles (8.7 %) conveyed the design effect less than 1.0, 22 articles (31.9 %) carried the design effect of 1.0 and 4 articles (5.8 %) carried the design effect of more than 1.0., which directed that larger sample size is always required to calculate correct HIV prevalence. As mentioned by many researchers, it was of utmost importance to carry out a detailed formative evaluation of network characteristics and occupational differentials of this high-risk group before deciding whether RDS was feasible or not. After deciding to introduce RDS, the next step should be thorough rapport building (through key informant interview or consultation meeting or both) with the community, and selection of seed and venue (location and timing) through proper guidance from community representatives. 91 https://doi.org/10.26555/eshr.v3i1.3629 Bhatta et. al (Accumulation of Biological and Behavioral Data of Female Sex Workers …) 10.26555/eshr.v6i2.9845 Table 1. Methodological and analytical data extracted from previously published articles. Author Year Country Pre-survey assessment No. of sites Interview method Initial seeds Final seeds Primary incentives ($) Secondary incentives ($) Target sample size Final sample size Maximum no. of waves Duration of data collection (week) Data adjusted Lowest age limits (FSW) Inconsistent condom use (%) African Region (AFR) Abdelrahim et al. 2010 Sudan NR 1 IA NR NR 10 10 NR 321 NR 8 Yes NR NR Vandenhoudt, et al 2013 Kenya Yes 1 ACASI 15 NR 4 1.25 480 481 6 12 Yes NR NR Johnston, et al. 2013 Mauritius NR 2 IA 5 5 17.5 7 NR 299 8 2 Yes NR NR Fonner et al. 2014 Swaziland Yes 1 IA 3 9 3 2.5 324 325 NR 20 NR 18 17.84 Baral et al. 2014 Swaziland Yes 1 IA NR NR NR NR NR 328 NR 12 No 18 61.7 Yam et al. 2014 Swaziland Yes 1 IA NR NR NR NR NR 325 NR 12 Yes 16 NR Musyoki et al. 2015 Kenya Yes 1 NR 6 NR 2 2 600 596 10 8 Yes 18 35.4 Schwitters et al. 2015 Uganda Yes 1 ACASI 4 NR 4 1.25 1500 1501 25 36 Yes 15 40 Mtetwa et al. 2015 Zimbabwe Yes 3 IA 22 22 5 2 NR 836 6 48 NR 18 NR Holland 2016 Burkina Faso NR 2 IA 10 10 3 4 700 694 NR 28 Yes 18 NR Quaife et al. 2016 South Africa Yes 1 IA 7 10 3.14 1.26 200 200 NR 24 No 16 NR Holland et al. 2016 Togo NR 2 IA 10 10 101 10 700 679 NR 28 Yes 18 NR Hargreaves et al. 2016 Zimbabwe NR 14 CASI 4 9 NR NR 2800 2800 5 20 Yes 18 NR Ouedraogo et al. 2017 Burkina Faso Yes 5 IA 3 10 4 3 NR 471 NR 64 Yes 18 37.7 92Vol. 6, No. 2, 2024, pp. 87-105 https://doi.org/10.26555/eshr.v3i1.3629 Bhatta et. al (Accumulation of Biological and Behavioral Data of Female Sex Workers …) 10.26555/eshr.v6i2.9845 Lafort et al. 2017 Kenya Yes 1 IA 16 16 NR NR 400 400 NR 12 Yes NR NR Lafort et al. 2017 Mozambique Yes 1 IA 13 13 NR NR 400 308 NR 12 Yes NR NR Lafort et al. 2017 South Africa Yes 1 IA 11 11 NR NR 400 458 NR 12 Yes NR NR Amogne et al. 2019 Ethiopia Yes 11 IA NR NR 5 2.5 4400 4900 NR 24 Yes 15 25.5 Twahirwa Rwema et al. 2019 Senegal NR 3 IA 12 12 NR NR NR 758 14 12 Yes 18 48 Parmley et al. 2019 South Africa Yes 2 IA; CAPI 30 30 9.5 4.5 400 410 NR 28 No 18 NR Lasater et al. 2019 Togo Yes 1 NR 5 5 NR NR 350 3545 NR 28 Yes 18 NR Chabata et al. 2019 Zimbabwe Yes 14 IA 6 8 NR NR 2800 2883 5 16 NR 18 39.2 Cowan et al. 2019 Zimbabwe Yes 19 NR NR NR 5 2 NR 6096 7 6 years Yes 18 28.3 Fearon et al. 2019 Zimbabwe No 7 NR 6 8 NR NR NR 1439 5 92 Yes 18 81 Owen et al. 2020 eSwatini NR 1 IA 14 14 NR NR 325 325 7 12 Yes 16 66.5 Jonas et al. 2020 Namibia Yes 4 ACASI 33 52 10 2 NR 1188 15 48 Yes 18 71.6 Hakim et al. 2020 Sudan Yes 1 CASI 4 9 20 21 NR 838 17 20 Yes 15 19.8 Chabata et al. 2020 Zimbabwe NR 6 IA 6 10 3 2 1810 1842 NR 24 18 19.6 Boothe et al. 2021 Mozambique Yes 1 IA 13 13 NR NR 400 308 NR 12 Yes 15 NR Bitty- Anderson et al. 2021 Togo Yes 1 IA NR NR NR NR 348 1036 NR 8 No 18 45.8 Yeo et al. 2022 South Africa Yes 2 IA; CASI 11 11 19 1.5 NR 664 NR 32 No 18 NR Hakim et al. 2022 Sudan Yes 2 IA 4 9 20 21 NR 838 NR 56 Yes 15 38 93Vol.6, No.2, 2024, pp.87-105 https://doi.org/10.26555/eshr.v3i1.3629 Bhatta et. al (Accumulation of Biological and Behavioral Data of Female Sex Workers …) 10.26555/eshr.v6i2.9845 Bitty- Anderson et al. 2022 Togo Yes 8 IA NR NR NR NR 495 1036 NR 12 No 18 33.7 Region of the Americas (AMR) Damacena et al. 2011 Brazil Yes 10 ACASI 2 4 2 1 2500 2523 6 48 Yes 18 NR Damacena et al. 2011 Brazil NR NR ACASI 5 5 NR 4 300 289 NR 52 NO NR NR Johnston et al. 2012 Honduras Yes 1 ACASI 5 5 2 3.5 200 182 11 8 Yes NR NR Dennis et al. 2013 El Salvador NR NR CASI, IA 10 10 NR NR NR 787 NR NR NO NR NR Lima et al. 2017 Brazil Yes 10 ACASI 5 10 NR NR 1000 2523 NR 48 Yes 18 NR Ferreira- Janior et al. 2018 Brazil Yes 12 IA 5 10 NR NR 4200 4245 NR 20 Yes 18 NR Martins et al. 2018 Brazil Yes 2 CAPI 5 5 3.02 2.01 400 402 NR 16 NR 18 NR Szwarcwald et al. 2018 Brazil Yes 12 IA 5 10 5 2.5 4200 4328 NR 20 Yes 18 NR Braga et al. 2021 Brazil Yes 12 SA NR NR NR NR 4200 4328 NR 24 Yes 18 NR Kolling et al. 2021 Brazil Yes 12 SA NR NR NR NR 4200 4328 NR 24 Yes 18 NR Matteoni et al. 2021 Brazil Yes 12 IA 5 10 5 2.5 4200 4328 NR 20 Yes 18 NR South-East Asian Region (SEAR) Blankenship et al. 2010 India Yes 1 IA 5 5 NR NR NR 1485 NR 12 Yes 24 NR Gupta et al., 2011 India Yes 1 IA NR NR NR NR NR 812 NR 12 Yes NR NR Barua et al. 2012 India NR NR SA 10 10 NR NR 400 426 11 8 NO NR NR Erausquin et al. 2012 India No 1 IA 5 5 0 0 2335 2276 NR 40 Yes 18 38.8 Medhi et al. 2012 India Yes 1 IA 10 9 NR NR 400 426 11 8 NO NR NR 94Vol.6, No.2, 2024, pp.87-105 https://doi.org/10.26555/eshr.v3i1.3629 Bhatta et. al (Accumulation of Biological and Behavioral Data of Female Sex Workers …) 10.26555/eshr.v6i2.9845 Armstrong et al. 2013 India Yes 1 IA NR NR NR NR 400 426 NR NR Yes 18 55.8 Lafort et al. 2016 India Yes 1 IA 8 8 NR NR 400 400 NR 12 Yes NR Reed et al. 2016 India NR 3 IA NR NR 4.7 NR NR 2335 NR 12 NR 18 NR Manathunge et al. 2020 Sri Lanka Yes 3 IA 2 7 2 1 1100 1180 9 20 Yes 18 20 European Region (EUR) Zohrabyan et al. 2013 Moldova NR NR IA 5 5 16 12 350 299 6 16 Yes NR NR Wirtz et al. 2015 Russia Yes 3 IA NR NR NR NR NR 754 NR 12 NR 18 14.6 McLaughlin et al. 2019 Armenia Yes 3 IA NR NR 7 3 NR NR 9 24 NR 18 NR Jonsson et al. 2019 Sweden Yes 1 IA 57 34 11 NR 595 415 15 21 Yes 18 NR Eastern Mediterranean Region (EMR) Mahfoud et al. 2010 Lebanon NR NR NR NR NR 6.6 2 NR 81 NR NR Yes NR NR Kriitmaa, et al. 2010 Somalia NR 1 IA w/ CAPI 6 NR 4 3 146 237 NR 8 Yes NR NR Valadez et al. 2013 Libya Yes 1 IA NR 13 NR NR 314 69 10 20 Yes NR NR Ahmadi et al. 2012 Iran Yes 8 IA N N 0 0 NR 144 NR 48 NR 18 19 Navadeh et al. 2012 Iran NR 1 IA 8 12 4 2 NR 177 NR 16 Yes NR NR Johnston et al. 2015 Morocco Yes 4 IA 4 10 NR NR NR 1447 10 8 Yes 18 NR Western Pacific Region (WPR) Li et al. 2010 China No 1 ACASI; IA 3 4 0 0 NR 320 16 20 Yes 16 82.6 Li et al. 2012 China NR 1 NR NR 3 16 8 NR NR 20 16 Yes 15 NR Yamanis et al 2013 China Yes 1 IA 7 7 19.66 12.1 454 515 11 16 NR 18 0 Liu et al. 2016 China NR 3 NR NR 3 16 8 NR 1245 20 16 Yes 15 NR 95Vol.6, No.2, 2024, pp.87-105 https://doi.org/10.26555/eshr.v3i1.3629 Bhatta et. al (Accumulation of Biological and Behavioral Data of Female Sex Workers …) 10.26555/eshr.v6i2.9845 Guida et al. 2019 China Yes 3 CAI 4 5 10 3 1200 1245 11 12 No 35 37.2 Weikum etal. 2019 Papua New Guinea Yes 3 IA 5 5 12 2 2100 2091 NR 28 No 12 NR Hakim et al. 2020 Papua New Guinea Yes 1 IA 5 9 14 4.5 700 674 NR 20 Yes 12 6 Willie et al. 2021 Papua New Guinea Yes 2 NR NR NR NR NR NR 2091 NR 20 NR 12 NR NR: not reported IA: interviewer administered SA: self-administered CASI: computer assisted structured interview ACASI: computer assisted structured interview CAPI: computer-assisted personal interviewing 96Vol.6, No.2, 2024, pp.87-105 https://doi.org/10.26555/eshr.v3i1.3629 Epidemiology and Society Health Review| ESHR ISSN 2656-6052 (online) | 2656-1107 (print) 10.26555/eshr.v6i2.9845 Here, we like clear that key informants are individuals who have significant and specialized knowledge about the community. This knowledge may stem from their professional roles, personal experiences, or long-term engagement with the community. They are often consulted in qualitative research and needs assessments to provide in-depth information, perspectives, and contextual understanding that might not be accessible through other data collection methods. The number of seeds should be guided by population size and the type of networking within it. Utmost care should be taken not to miss selected geographical pockets while distributing the seeds. Considering the stigmatization and social isolation associated with this occupation, sensitization of administrative and legal officials is an essential prerequisite before initiating the data collection.88 Figure 2. Published articles of RDS surveys were conducted in the WHO demarcated regions DISCUSSION It is essential to explain the methodological and analytical aspects of RDS in any study through the survey strategy, execution, and examination, which are necessary to evaluate the RDS surveys and their findings.84 The majority of surveys, accumulated here reported the most vital information as the place/country of study, study year, population sampled, methods of interview, and final sample size. RDS adjustment consists of applying variable-specific weights to account for the potential biases arising due to homophily and the variation in network sizes of different individuals.89 Recent advance in software-based weighted analysis has made the opportunity to obtain a much more robust estimate that approximates random sampling if it fulfils certain assumptions.90 It is evident that providing compensation to the respondents increases the rate of recruitment. Moreover, secondary compensation increases the rate of recruitment in comparison with the single compensation system.79 However, several published articles, also mentioned that their 97 Vol. 6, No. 2, 2024, pp. 87-105 https://doi.org/10.26555/eshr.v3i1.3629 Bhatta et. al (Accumulation of Biological and Behavioral Data of Female Sex Workers …) 10.26555/eshr.v6i2.9845 field team got physically assaulted to denied some respondents, who were willing to participate to avail the incentive without being eligible as a participant, and argued for providing more money as secondary incentive.91 This tendency of avail extra money, encourages respondent to give multiple responses at different RDS venues. Sometime a single responder can get coupon from two different typologies. Suppose, an FSW person who inject drugs can get coupon from FSW RDS site as well as from FIDU RDS site. FIDU refers here female who inject drugs. These undesirable events could be prevented by strong inter-sectoral communication and convergence before initiating the field activity, and by judiciously using screening tools to prevent duplication 84,92. Different groups of workers are also cited that documentation of refusal rate is difficult in RDS,26 which may be solved by using the different indicators for assessing the speed of recruitment process82,83. Survey conductors must monitor the coupon return rate, in such a way that they can modify the number of seeds accordingly to rate the data collection to complete the survey within a stipulated time.27 Difficulties in accessing FSW with higher social status is a general limitation any sampling designs used (time location cluster sampling, conventional cluster sampling, snowball sampling etc), till date.83 For public health perspective, they are expected to be having sufficient knowledge on regular health and hygiene, more empowered to convince condom use, and less likely to disclose their status and come under the umbrella of government/NGO- run free health services, so they are unlikely to get included in this kind of activities.83 The advantage of RDS over other methods for sampling similar populations, is that it can reach hidden population networks that the other methods fail to reach.21 Despite non-random selection of initial seeds, this sampling can produce weighted estimates which can approximate random sampling if certain assumptions are fulfilled.81 The use of RDS in recruiting different population has been increasing multi fold in recent years. This sampling technique largely depends on social networks and it can be effective to recruit those populations that are expected to be linked by their social network, like injecting Drug Users (IDUs) or Men who have sex with Men (MSMs). Literature review revealed that there has been an increasing number of research activities in the current year where the present sampling technique was used for recruiting Female Sex Workers.81-83 Sex workers are a highly vulnerable occupational group, involved in selling sex for money or kind. Globally in most of the countries, sex work is not a socially acceptable occupation, and sex workers face considerable stigma and discrimination. They are likely to have a social network because of their need to be united to fight against occupational vulnerability. A counter argument can also be raised. FSWs are distinct occupational groups, each of them is a potential competitor for other group members. Networking within FSW is not essential for continuing their occupation, rather they need networking with pimps and clients for their sustainability. So, a considerable variation in their social connectivity is expected among this population group. As RDS largely relies on social networks, it will be interesting to know whether RDS is useful to recruit FSWs, and what type of challenges that could be faced by the researchers if they want to recruit FSWs with RDS.85 Like any systematic review, the present study is also restricted by the comprehensiveness of the published articles and whether workers published their study in open accessed and peer- reviewed journals. Moreover, included articles having surveys that accumulate biological data leaving an approach for further assessment of those surveys that described RDS on FSW population and give any information on biological data.86 It was found, that the number of articles regarding RDS surveys on FSW is much lower than the number of surveys were 98Vol. 6, No. 2, 2024, pp. 87-105 https://doi.org/10.26555/eshr.v3i1.3629 Bhatta et. al (Accumulation of Biological and Behavioral Data of Female Sex Workers …) Vol. 6, No. 2, 2024, pp. 87-105 10.26555/eshr.v6i2.9845 conducted. One of the important findings of the present study is that published articles are devoid of essential data regarding RDS which supports the need to homogeneously report results from RDS surveys that limited the scope of analyses and acquaint with uncertainty in some of the other outcomes.89 The articles are excluded, undoubtedly not fulfilling the necessary features of the RDS method. However, two to three articles were included that did not incorporate all the features of RDS, showing the incompleteness of reporting.90 On those occasions, surveys were categorized as using RDS up to some extent. It was found that seventy-five articles claimed to use RDS, but did not, reported using a ‘modified’ or ‘mixed methods’ of RDS.91 These studies are not providing any definite indication of the assemblage and use of the personal network, size data, recruitment treaties, coupon management along with numerous recruitment waves. These articles are not included in the final analysis. A few extracted publications were found with significant limitations, including less competent staff, several ineligible persons were trying to participate in the survey and compelled to close or move survey sites at the period of data collection. These articles are used to make a note on the challenges of implementing RDS among FSW and recommendations was suggested from same or from other similar published articles on RDS among FSW.92 The majority of published surveys were from African Region (AFR) and the south-east Asian Region (SEAR); it may be useful to find more publications on RDS survey on FSWs from other regions. The socio-economic position of FSW from these regions may have an impact on the survey procedure using RDS, regarding the networking among subjects and incentives may have a role here.82 CONCLUSION It was found through the present review that most of the published articles were largely successful to recruit FSWs through RDS, with the varying response rate in almost all the study settings globally. Despite ample pieces of evidence of challenges in implementing RDS among FSW and threats of selection bias during the sampling process, this technique is regarded as the most suitable technique available till date for sampling those populations where the sampling frame is non-existing. The key advantage is that RDS offers a systematic and theoretically grounded approach to recruiting participants from “hidden” or “hard to reach” populations. This peer-to-peer recruitment is driven by anonymous coupons, making it successful among populations that are stigmatized or practice those behaviours considered illegal in the existing social structure. As sex work also carries similar occupational vulnerability, this approach is expected to be appropriate and the best suited for this high-risk population. Present findings will help researchers, policymakers and service providers to improve RDS methods for surveillance of any key population by providing a minimum set of parameters of specific methodological, analytical, and testing procedures including RDS methods to evaluate the overall quality of any RDS survey. Authors' contribution MB, SiB and SuB conceived and designed the study. MB, SD and DC established the search strategy. PG, AM, MB and SS prepare the master table. MB and PG extracted the data. MB and SiB perform the analysis. MB, AM, PG, SiB, SuB and SD wrote the article. All the authors read the manuscript before they have given the final approval for publication. 99 https://doi.org/10.26555/eshr.v3i1.3629 Bhatta et. al (Accumulation of Biological and Behavioral Data of Female Sex Workers …) Vol. 6, No. 2, 2024, pp. 87-105 10.26555/eshr.v6i2.9845 Funding This research has not received external funding for research. 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