Comparing snowball sampling and RDS: A methodology and case study

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Authors: Dongah Kim, Krista J. Gile, Bradley Mathers, Massimo Mirandola, Lorenzo Gios, Igor Toskin, Keith Sabin
Cited by: 3
References: 20

Abstract

Both snowball sampling and Respondent Driven Sampling (RDS) are used to sample hard-to-reach populations. Snowball sampling was initially developed as a probability sampling method, but in practice, it is widely used as a non-probabilistic sampling method. RDS was developed to address the limitations of snowball sampling and can be used to approximate a probability sampling method in practice. Therefore, RDS is often recommended for bio-behavioral surveys (BBS) for surveillance of HIV, viral hepatitis, and STIs among key populations. In some settings, simpler and cheaper monitoring are desired. WHO and UNAIDS are developing a simplified and rapid bio-behavioral survey methodology, a version of snowball sampling to use when RDS is infeasible. In this paper, we use data-based simulations to examine the potential similarities and differences between results from a snowball sample with recruitment initiated from a health service and samples recruited through RDS methodology.

Fields of Study & Subjects

HIV Drug Use Sexual Risk Census and Population Estimation Survey Methodology and Nonresponse

Publication details

Journal / source
PLoS ONE
Publisher
Public Library of Science (PLoS)
Volume
21
Issue
1
Pages
e0331666–e0331666
Publication date
14 January 2026
Language
EN