Literature DB >> 23486495

Incorporating the service multiplier method in respondent-driven sampling surveys to estimate the size of hidden and hard-to-reach populations: case studies from around the world.

Lisa G Johnston1, Dimitri Prybylski, H Fisher Raymond, Ali Mirzazadeh, Chomnad Manopaiboon, Willi McFarland.   

Abstract

BACKGROUND: Estimating the sizes of populations at highest risk for HIV is essential for developing and monitoring effective HIV prevention and treatment programs. We provide several country examples of how service multiplier methods have been used in respondent-driven sampling surveys and provide guidance on how to maximize this method's use.
METHODS: Population size estimates were conducted in 4 countries (Mauritius- intravenous drug users [IDU] and female sex workers [FSW]; Papua New Guinea-FSW and men who have sex with men [MSM]; Thailand-IDU; United States-IDU) using adjusted proportions of population members reporting attending a service, project or study listed in a respondent-driven sampling survey, and the estimated total number of population members who visited one of the listed services, projects, or studies collected from the providers.
RESULTS: The median population size estimates were 8866 for IDU and 667 for FSW in Mauritius. Median point estimates for FSW were 4190 in Port Moresby and 8712 in Goroka, Papua New Guinea, and 2,126 for MSM in Port Moresby and 4200 for IDU in Bangkok, Thailand. Median estimates for IDU were 1050 in Chiang Mai, Thailand, and 15,789 in 2005 and 15,554 in 2009 in San Francisco.
CONCLUSION: Our estimates for almost all groups in each country fall within the range of other regional and national estimates, indicating that the service multiplier method, assuming all assumptions are met, can produce informative estimates. We suggest using multiple multipliers whenever possible, garnering program data from the widest possible range of services, projects, and studies. A median of several estimates is likely more robust to potential biases than a single estimate.

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Year:  2013        PMID: 23486495     DOI: 10.1097/OLQ.0b013e31827fd650

Source DB:  PubMed          Journal:  Sex Transm Dis        ISSN: 0148-5717            Impact factor:   2.830


  40 in total

1.  Population Size Estimates of Street Children in Iran: Synthesis of Multiple Methods.

Authors:  Meroe Vameghi; Payam Roshanfekr; Delaram Ali; Mehdi Noroozi; Saied Madani; Willi McFarland; Ali Mirzazadeh
Journal:  J Urban Health       Date:  2019-08       Impact factor: 3.671

2.  A Bayesian approach to synthesize estimates of the size of hidden populations: the Anchored Multiplier.

Authors:  Paul D Wesson; Ali Mirzazadeh; Willi McFarland
Journal:  Int J Epidemiol       Date:  2018-10-01       Impact factor: 7.196

3.  If You Are Not Counted, You Don't Count: Estimating the Number of African-American Men Who Have Sex with Men in San Francisco Using a Novel Bayesian Approach.

Authors:  Paul Wesson; Mark S Handcock; Willi McFarland; H Fisher Raymond
Journal:  J Urban Health       Date:  2015-12       Impact factor: 3.671

4.  Population Size Estimation of Men Who Have Sex with Men in Ho Chi Minh City and Nghe An Using Social App Multiplier Method.

Authors:  Ali Safarnejad; Nguyen Thien Nga; Vo Hai Son
Journal:  J Urban Health       Date:  2017-06       Impact factor: 3.671

5.  How Many Transgender Men Are There in San Francisco?

Authors:  Willi McFarland; Erin Wilson; H Fisher Raymond
Journal:  J Urban Health       Date:  2018-02       Impact factor: 3.671

6.  Estimating hidden population size using Respondent-Driven Sampling data.

Authors:  Mark S Handcock; Krista J Gile; Corinne M Mar
Journal:  Electron J Stat       Date:  2014       Impact factor: 1.125

7.  Using Population-Size Estimation and Cross-sectional Survey Methods to Evaluate HIV Service Coverage Among Key Populations in Burkina Faso and Togo.

Authors:  Claire E Holland; Seni Kouanda; Marcel Lougué; Vincent Palokinam Pitche; Sheree Schwartz; Simplice Anato; Henri Gautier Ouedraogo; Jules Tchalla; Clarence S Yah; Laurent Kapesa; Sosthenes Ketende; Chris Beyrer; Stefan Baral
Journal:  Public Health Rep       Date:  2016-11-14       Impact factor: 2.792

8.  Estimating the Size of Hidden Populations Using Respondent-driven Sampling Data: Case Examples from Morocco.

Authors:  Lisa G Johnston; Katherine R McLaughlin; Houssine El Rhilani; Amina Latifi; Abdalla Toufik; Aziza Bennani; Kamal Alami; Boutaina Elomari; Mark S Handcock
Journal:  Epidemiology       Date:  2015-11       Impact factor: 4.822

9.  Use of Population-Based Surveys for Estimating the Population Size of Persons Who Inject Drugs in the United States.

Authors:  Heather Bradley; Elizabeth M Rosenthal; Meredith A Barranco; Tomoko Udo; Patrick S Sullivan; Eli S Rosenberg
Journal:  J Infect Dis       Date:  2020-09-02       Impact factor: 5.226

10.  Diagnostics for Respondent-driven Sampling.

Authors:  Krista J Gile; Lisa G Johnston; Matthew J Salganik
Journal:  J R Stat Soc Ser A Stat Soc       Date:  2014-05-01       Impact factor: 2.483

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