Comparing snowball sampling and RDS: A methodology and case study
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.
Authors
- Krista J. Gile
- Bradley Mathers
- Dongah Kim (ORCID: https://orcid.org/0000-0003-4638-7514)
- Keith Sabin (ORCID: https://orcid.org/0000-0002-2290-8621)
- Igor Toskin
- Massimo Mirandola
- Lorenzo Gios
Institutions
- University of Verona (IT)
- Joint United Nations Programme on HIV/AIDS (CH)
- Amherst College (US)
- University of Massachusetts Amherst (US)
- World Health Organization (CH)
- The University of Texas at Austin (US)
Publication Details
- Journal
- PLoS ONE
- Published
- 2026-01-14
- DOI
- https://doi.org/10.1371/journal.pone.0331666
- Citations
- 1
- Primary Topic
- HIV, Drug Use, Sexual Risk
- Type
- article
- Field-Weighted Citation Impact
- 31.52