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Model-based Respondent-driven sampling analysis for HIV prevalence in brazilian MSM

Authors
  • Robineau, Olivier1, 2
  • Gomes, Marcelo F. C.3
  • Kendall, Carl4
  • Kerr, Ligia5
  • Périssé, André6
  • Boëlle, Pierre-Yves1, 7
  • 1 INSERM, Sorbonne Université, Institut Pierre Louis d’Épidémiologie et de Santé Publique, Paris, F75012, France , Paris (France)
  • 2 Service Universitaire des Maladies Infectieuses et du Voyageur, Tourcoing, France , Tourcoing (France)
  • 3 Fundação Oswaldo Cruz (Fiocruz), Programa de Computação Cientifica, Rio de Janeiro, Brazil , Rio de Janeiro (Brazil)
  • 4 Tulane University, New Orleans, Louisiana, USA , Louisiana (United States)
  • 5 Federal University of Ceará, Fortaleza, Brazil , Fortaleza (Brazil)
  • 6 Departamento de Ciências Biológicas, Rio de Janeiro, RJ, Brazil , Rio de Janeiro (Brazil)
  • 7 Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique, AP-HP, Hôpital Saint-Antoine, Santé publique, Paris, F75012, France , Paris (France)
Type
Published Article
Journal
Scientific Reports
Publisher
Springer Nature
Publication Date
Feb 14, 2020
Volume
10
Issue
1
Identifiers
DOI: 10.1038/s41598-020-59567-2
Source
Springer Nature
License
Green

Abstract

Respondent Driven Sampling study (RDS) is a population sampling method developed to study hard-to-reach populations. A sample is obtained by chain-referral recruitment in a network of contacts within the population of interest. Such self-selected samples are not representative of the target population and require weighing observations to reduce estimation bias. Recently, the Network Model-Assisted (NMA) method was described to compute the required weights. The NMA method relies on modeling the underlying contact network in the population where the RDS was conducted, in agreement with directly observable characteristics of the sample such as the number of contacts, but also with more difficult-to-measure characteristics such as homophily or differential characteristics according to the response variable. Here we investigated the use of the NMA method to estimate HIV prevalence from RDS data when information on homophily is limited. We show that an iterative procedure based on the NMA approach allows unbiased estimations even in the case of strong population homophily and differential activity and limits bias in case of preferential recruitment. We applied the methods to determine HIV prevalence in men having sex with men in Brazilian cities and confirmed a high prevalence of HIV in these populations from 3.8% to 22.1%.

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