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

• Published in: Scientific reports Vol. 10; no. 1; p. 2646
• Main Authors: Robineau, Olivier, Gomes, Marcelo F. C., Kendall, Carl, Kerr, Ligia, Périssé, André, Boëlle, Pierre-Yves
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 14.02.2020; Nature Publishing Group
• Subjects: 692/699/255/1901; 692/700/478/174; Bias; Brazil - epidemiology; Computer Simulation; Estimates; HIV; HIV Infections - epidemiology; Homosexuality, Male; Human health and pathology; Human immunodeficiency virus; Humanities and Social Sciences; Humans; Infectious diseases; Life Sciences; Male; Methods; Microbiology and Parasitology; Models, Biological; multidisciplinary; Population Density; Population sampling; Population studies; Prevalence; Random variables; Sampling; Santé publique et épidémiologie; Science; Science (multidisciplinary); Seeds; Sexually transmitted diseases; Simulation; STD; Surveys and Questionnaires; Virology; Brazil; Epidemiology; HIV infections
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-020-59567-2

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%.