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Cutting edge methodology
P1-25 Potential bias in HIV estimates using RDS sampling
  1. M Guimaraes,
  2. C Machado
  1. Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil

Abstract

Introduction Respondent-driven sampling (RDS) is a process used to collect data from hard-to-reach populations, such as men who have sex with men (MSM). This is a process of accessing a hidden population of interest via following links in the network of acquaintances belonging to the population, and it can be a useful epidemiological tool for estimating HIV prevalence in high risk populations. However, a typical sample arising from an RDS process on a network contains a certain degree of homophily, and in case the quantity surveyed is a given characteristic, this can generate biased results.

Methods A cross-sectional study was conducted in Belo Horizonte, Brazil, in order to estimate the HIV prevalence among MSM in 2009. Recruitment was carried out using RDS sampling. We assessed whether HIV status of the recruiter was associated with HIV status of the recruitee. Statistical analysis was carried out by McNemar's χ2.

Results We analysed 221 recruiter-recruitee pairs among the 274 MSM included in the study. The prevalence of HIV infection was 10.8% (95% CI 4.5 to 17.8). The probability of recruiting an HIV positive individual was 80% when the recruiter was also HIV positive and 8.3% when the recruiter was HIV negative, indicating a dependency on HV status during the recruitment process (McNemar=13.5, p<0.001).

Conclusion Although RDS sampling may be suitable for ascertaining HIV prevalence among hidden populations, these estimates are likely to be biased and results should be carefully assessed and proper adjustments carried out.

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