Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom; Department of International Health and Development, Center for Global Health Equity, Tulane University School of Public Health and Tropical Medicine, Canal Street, New Orleans, LA 70112, United States; Research Department of Infection and Population Health, University College London, Gower Street, London, WC1E 6BT, United Kingdom; MRC/UVRI Uganda Research Unit on AIDS, Entebbe, Uganda; School of International Development, University of East Anglia, Norwich, NR4 7TJ, United Kingdom; Department of Veterinary Medicine, University of Cambridge, Madingley Road, CB3 0ES, United Kingdom
McCreesh, N., Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom; Johnston, L.G., Department of International Health and Development, Center for Global Health Equity, Tulane University School of Public Health and Tropical Medicine, Canal Street, New Orleans, LA 70112, United States; Copas, A., Research Department of Infection and Population Health, University College London, Gower Street, London, WC1E 6BT, United Kingdom; Sonnenberg, P., Research Department of Infection and Population Health, University College London, Gower Street, London, WC1E 6BT, United Kingdom; Seeley, J., Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom, MRC/UVRI Uganda Research Unit on AIDS, Entebbe, Uganda, School of International Development, University of East Anglia, Norwich, NR4 7TJ, United Kingdom; Hayes, R.J., Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom; Frost, S.D.W., Department of Veterinary Medicine, University of Cambridge, Madingley Road, CB3 0ES, United Kingdom; White, R.G., Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom
Background: Respondent-driven sampling(RDS) is an increasingly widely used variant of a link tracing design for recruiting hidden populations. The role of the spatial distribution of the target population has not been robustly examined for RDS. We examine patterns of recruitment by location, and how they may have biased an RDS study findings.Methods: Total-population data were available on a range of characteristics on a population of 2402 male household-heads from an open cohort of 25 villages in rural Uganda. The locations of households were known a-priori. An RDS survey was carried out in this population, employing current RDS methods of sampling and statistical inference.Results: There was little heterogeneity in the population by location. Data suggested more distant contacts were less likely to be reported, and therefore recruited, but if reported more distant contacts were as likely as closer contacts to be recruited. There was no evidence that closer proximity to a village meeting place was associated with probability of being recruited, however it was associated with a higher probability of recruiting a larger number of recruits. People living closer to an interview site were more likely to be recruited.Conclusions: Household location affected the overall probability of recruitment, and the probability of recruitment by a specific recruiter. Patterns of recruitment do not appear to have greatly biased estimates in this study. The observed patterns could result in bias in more geographically heterogeneous populations. Care is required in RDS studies when choosing the network size question and interview site location(s). © 2011 McCreesh et al; licensee BioMed Central Ltd.