title: Putting respondent-driven sampling on the map: insights from Rio de Janeiro, Brazil.
abstract: BACKGROUND
  Hard-to-reach populations with high background infection rates for HIV are particularly relevant in countries with restricted HIV epidemics, such as Brazil, where the very dynamics of the epidemic depends on the bridges between those populations and the general population. Respondent-driven sampling (RDS) has been one of the key strategies to assess such populations and inform policy making.
  
  
  OBJECTIVE
  To geocode and visualize an RDS-based study on 605 heavy drug users, conducted in Rio de Janeiro, in 2009.
  
  
  METHODS
  The location and characteristics of the residence of interviewees were collected by an Audio Computer-Assisted Self Interview (ACASI) survey, supplemented by additional information. Place of residence was geocoded and depicted as network graphs and thematic maps.
  
  
  RESULTS
  The geographic distribution of the interviewees was found to be very heterogeneous. The recruiting chains progressed slowly during the successive waves toward neighborhoods far from the initial geographic axis. Despite the undeniable progress toward a broader geographic scope as the study proceeded through 11 successive waves, some key geographic areas were excluded.
  
  
  CONCLUSIONS
  In the context of a large and complex urban area, plagued by structural violence and with a lively drug scene, the study made evident network bottlenecks. Either secondary to its relatively small sample size, structural constraints, or a combination of both, such bottlenecks represent a formidable challenge for RDS or other network-based methods as applied to urban settings with characteristics similar to Rio de Janeiro.
authors.forename: Lidiane
authors.initials: L
authors.lastname: Toledo
authors.forename: Cláudia T
authors.initials: CT
authors.lastname: Codeço
authors.forename: Neilane
authors.initials: N
authors.lastname: Bertoni
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Albuquerque
authors.forename: Monica
authors.initials: M
authors.lastname: Malta
authors.forename: Francisco I
authors.initials: FI
authors.lastname: Bastos
mesh_terms: D001938:Brazil / Q000453:epidemiology; D003625:Data Collection; D055030:Drug Users; D005260:Female; D005843:Geography; D015658:HIV Infections / Q000453:epidemiology*; D006801:Humans; D008297:Male