Please use this identifier to cite or link to this item: https://www.arca.fiocruz.br/handle/icict/4259
Title: Analysis of Data Collected by RDS Among Sex Workers in 10 Brazilian Cities, 2009: Estimation of the Prevalence of HIV, Variance, and Design Effect
Authors: Szwarcwald, Celia Landmann
Junior, Paulo Roberto Borges de Souza
Damacena, Giseli Nogueira
Junior, Aristides Barbosa
Kendall, Carl
Affilliation: Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Científica e Tecnológica em Saúde. Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Científica e Tecnológica em Saúde. Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Científica e Tecnológica em Saúde. Rio de Janeiro, RJ, Brasil.
Ministério da Saúde. Programa Nacional de DST e Aids. Assessoria de Avaliação. Brasília, DF, Brasil.
Tulane University. Department of Community Health Sciences. Center for Global Health Equity. New Orleans, LA, USA.
Abstract: Background: Respondent-driven sampling (RDS) is a chain- referral method that is being widely used to recruit most at-risk populations. Because the method is respondent driven, observations are dependent. However, few publications have focused on methodological challenges in the analysis of data collected by RDS. Methods: In this article, we propose a method for estimating the vari- ance of the HIV prevalence rate, based on the Markov transition prob- abilities and within recruitment cluster variation. The method was applied to a female commercial sex workers study carried out in 10 Brazilian cities in 2008. Both the inverse of network size and the size of the city were considered in the estimation of overall sampling weights. The study included a behavior questionnaire and rapid tests for HIV and syphilis. Results: About 2523 interviews were conducted successfully, excluding the seeds. Results show a positive homophily between recruits for those HIV+; HIV- recruiters selected HIV+ recruits 4% of the time; HIV+ recruiters selected other HIV+ recruits 19.6% of the time, about 5 times higher. The prevalence rate was estimated at 4.8% (95% confidence interval: 3.4 to 6.1), and a design effect of 2.63. Conclusions: Using statistical methods for complex sample designs, it was possible to estimate HIV prevalence, standard error, and the design effect analytically. Additionally, the proposed analysis lends itself to logistic regression, permitting multivariate models. The stratification in cities has proved suitable for reducing the effect of design and can be adopted in other RDS studies, provided the weights of the strata are known.
Keywords: Brazil
Complex sample
Design effect
FCSW
HIV prevalence
RDS
DeCS: HIV
Análise de Dados
Profissionais do Sexo
Estudos transversais / estatística & dados numéricos
Análise de Variância
Gráficos
Brasil /epidemiologia
Issue Date: 2011
Publisher: Lippincott, Williams & Wilkins
Citation: SZWARCWALD, Celia Landmann et al. Analysis of Data Collected by RDS Among Sex Workers in 10 Brazilian Cities, 2009: estimation of the Prevalence of HIV, Variance, and Design Effect. Journal of Acquired Immune Deficiency Syndromes, Philadelphia, v. 57, Suppl 3, p. 129-135, Aug. 2011.
DOI: 10.1097/QAI.0b013e31821e9a36
ISSN: 1525-4135
Copyright: open access
Appears in Collections:ICICT - Artigos de Periódicos

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