Article

Transfer of sampling methods for studies on most-at-risk populations (MARPs) in Brazil

Departamento de DST, AIDS e Hepatites Virais, Ministério da Saúde, Brasília, Brasil.
Cadernos de saúde pública / Ministério da Saúde, Fundação Oswaldo Cruz, Escola Nacional de Saúde Pública (Impact Factor: 0.89). 01/2011; 27 Suppl 1(Suppl 1):S36-44. DOI: 10.1590/S0102-311X2011001300005
Source: PubMed

ABSTRACT The objective of this paper was to describe the process of transferring two methods for sampling most-at-risk populations: respondent-driven sampling (RDS) and time-space sampling (TSS). The article describes steps in the process, the methods used in the 10 pilot studies, and lessons learned. The process was conducted in six steps, from a state-of-the-art seminar to a workshop on writing articles with the results of the pilot studies. The principal investigators reported difficulties in the fieldwork and data analysis, independently of the pilot sampling method. One of the most important results of the transfer process is that Brazil now has more than 100 researchers able to sample MARPs using RDS or TSS. The process also enabled the construction of baselines for MARPS, thus providing a broader understanding of the dynamics of HIV infection in the country and the use of evidence to plan the national response to the epidemic in these groups.

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Available from: Carl Kendall, Aug 10, 2015
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    • "Respondent-driven sampling (RDS) is a recently introduced link-tracking network sampling technique for collecting such information (Heckathorn, 1997). Because of the pressing need for information about the most at-risk groups and the weaknesses of alternatives approaches, RDS has already been used in more than 120 HIV-related studies in 20 countries (Malekinejad et al., 2008) and has been adopted by leading public health organizations, such as the US Centers for Disease Control and Prevention (CDC) (Barbosa Júnior et al., 2011; Lansky et al., 2007; Montealegre et al., 2012). "
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    ABSTRACT: Respondent-driven sampling (RDS) is a widely used method for sampling from hard-to-reach human populations, especially groups most at-risk for HIV/AIDS. Data are collected through a peer-referral process in which current sample members harness existing social networks to recruit additional sample members. RDS has proven to be a practical method of data collection in many difficult settings and has been adopted by leading public health organizations around the world. Unfortunately, inference from RDS data requires many strong assumptions because the sampling design is not fully known and is partially beyond the control of the researcher. In this paper, we introduce diagnostic tools for most of the assumptions underlying RDS inference. We also apply these diagnostics in a case study of 12 populations at increased risk for HIV/AIDS. We developed these diagnostics to enable RDS researchers to better understand their data and to encourage future statistical research on RDS.
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