Advertisement

AIDS and Behavior

, 12:97 | Cite as

An Empirical Comparison of Respondent-driven Sampling, Time Location Sampling, and Snowball Sampling for Behavioral Surveillance in Men Who Have Sex with Men, Fortaleza, Brazil

  • Carl Kendall
  • Ligia R. F. S. Kerr
  • Rogerio C. Gondim
  • Guilherme L. Werneck
  • Raimunda Hermelinda Maia Macena
  • Marta Kerr Pontes
  • Lisa G. Johnston
  • Keith Sabin
  • Willi McFarland
Original Paper

Abstract

Obtaining samples of populations at risk for HIV challenges surveillance, prevention planning, and evaluation. Methods used include snowball sampling, time location sampling (TLS), and respondent-driven sampling (RDS). Few studies have made side-by-side comparisons to assess their relative advantages. We compared snowball, TLS, and RDS surveys of men who have sex with men (MSM) in Forteleza, Brazil, with a focus on the socio-economic status (SES) and risk behaviors of the samples to each other, to known AIDS cases and to the general population. RDS produced a sample with wider inclusion of lower SES than snowball sampling or TLS—a finding of health significance given the majority of AIDS cases reported among MSM in the state were low SES. RDS also achieved the sample size faster and at lower cost. For reasons of inclusion and cost-efficiency, RDS is the sampling methodology of choice for HIV surveillance of MSM in Fortaleza.

Keywords

Sampling hidden populations Respondent-driven sampling Brazil Behavioral surveillance Sexual behavior HIV 

Notes

Acknowledgments

We wish to acknowledge the support of the University of California, San Francisco, Center for AIDS Prevention Studies, U.S. National Institute of Mental Health (NIMH), P30 MH062246; AIDS International Training in Research Program (AITRP), Fogarty International Center, D43TW00003; and the International Traineeships in AIDS Prevention Studies, U.S. NIMH, R25MH064712. This work was supported by the National AIDS Prevention Program of the Brazilian Ministry of Health and the Centers for Disease Control-Global AIDS Program through the University Technical Assistance Project, Tulane University (U62/CCU622410-01).

References

  1. ABEP (2005). Critério Econômico Brasil. http://www.gerp.com.br/Criterio.htm. Accessed 29 July 2007.
  2. Biernacki, P., & Waldorf, D. (1981). Snowball sampling: Problems and techniques of chain referral sampling. Sociological Methods Research, 10, 141–163.Google Scholar
  3. DATASUS (2006). http://www.aids.gov.br/cgi/tabcgi.exe/tabnet/ce.htm. Accessed 30 July 2006.
  4. Erickson, B. (1979). Some problems of inference from chain data. Sociological Methodology Research, 10, 276–302.CrossRefGoogle Scholar
  5. FHI (2000). Behavioral Surveillance Survey (BSS): guidelines for repeated behavioral surveys in population at risk of HIV. Family Health International. http://www.fhi.org/en/HIVAIDS/pub/guide/bssguidelines.htm. Accessed 29 July 2007.
  6. Heckathorn, D. D. (1997). Respondent-driven sampling: A new approach to the study of hidden populations. Social Problems, 44, 174–199.CrossRefGoogle Scholar
  7. Johnston, L. G., Khanam, R., Reza, M., Khan, S. I., Banu, S., Alam, M. S., Rahman, M., & Aziz, T. (2007). The effectiveness of respondent driven sampling for recruiting males who have sex with males in Dhaka, Bangladesh. AIDS and Behavior, August [epub ahead of publication].Google Scholar
  8. Kerr-Pontes, L. R., Gondim, R., Mota, R. S., Martins, T. A., & Wypij, D. (1999). Self-reported sexual behaviour and HIV risk taking among men who have sex with men in Fortaleza, Brazil. AIDS, 13, 709–717.PubMedCrossRefGoogle Scholar
  9. Magnani, R., Sabin, K., Saidel, T., & Heckathorn, D. (2005). Review of sampling hard-to-reach and hidden populations for HIV surveillance. AIDS, 19(Suppl 2), S67–S72.PubMedCrossRefGoogle Scholar
  10. Muhib, F. B., Lin, L. S., Stueve, A., Miller, R. L., Ford, W. L., Johnson, W. D., & Smith, P. J. (2001). A venue-based method for sampling hard-to-reach populations. Public Health Reports, 116(Suppl 1), 216–222.PubMedCrossRefGoogle Scholar
  11. Ramirez-Valles, J., Heckathorn, D. D., Vazquez, R., Diaz, R. M., & Campbell, R. T. (2005). From networks to populations: The development and application of respondent-driven sampling among IDUs and Latino gay men. AIDS and Behavior, 9, 387–402.PubMedCrossRefGoogle Scholar
  12. Salganik, M. J. (2006). Variance estimation, design effects, and sample eize calculations for respondent-driven sampling. Journal of Urban Health, 83, 98–112.CrossRefGoogle Scholar
  13. Salganik, M. J., & Heckathorn, D. D. (2004). Sampling and estimation in hidden populations using respondent-driven sampling. Sociological Methods Research, 34, 193–239.CrossRefGoogle Scholar
  14. Stueve, A., O’Donnell, L. N., Duran, R., San, D. A., & Blome, J. (2001). Time-space sampling in minority communities: Results with young Latino men who have sex with men. American Journal of Public Health, 91, 922–926.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Carl Kendall
    • 1
  • Ligia R. F. S. Kerr
    • 2
  • Rogerio C. Gondim
    • 3
  • Guilherme L. Werneck
    • 4
  • Raimunda Hermelinda Maia Macena
    • 5
  • Marta Kerr Pontes
    • 6
  • Lisa G. Johnston
    • 1
  • Keith Sabin
    • 7
  • Willi McFarland
    • 8
  1. 1.Department of International Health and Development, Center for Global Health EquityTulane University School of Public Health and Tropical MedicineNew OrleansUSA
  2. 2.Departamento de Saude ComunitariaUniversidade Federal do CearáFortalezaBrazil
  3. 3.Grupo de Apoio a Prevenção da AIDSFortalezaBrazil
  4. 4.Instituto de Medicina SocialUniversidade do Estado do Rio de JaneiroRio de JaneiroBrazil
  5. 5.Universidade Federal do CearáFortelezaBrazil
  6. 6.Departmento de PsicologiaUniversidade Federal do CearáFortelezaBrazil
  7. 7.Global AIDS Program, Centers for Disease ControlAtlantaUSA
  8. 8.Institute for Global HealthUniversity of CaliforniaSan FranciscoUSA

Personalised recommendations