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Lisa G Johnston, MA, MPH, PhD

Personal network size and respondent-driven sampling:Evidence from 12 studies in the Dominican Republic. Lisa G Johnston, MA, MPH, PhD Tulane University School of Public Health and Tropical Medicine, USA lsjohnston.global@gmail.com Matthew J. Salganik, PhD

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Lisa G Johnston, MA, MPH, PhD

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  1. Personal network size and respondent-driven sampling:Evidence from 12 studies in the Dominican Republic Lisa G Johnston, MA, MPH, PhD Tulane University School of Public Health and Tropical Medicine, USA lsjohnston.global@gmail.com Matthew J. Salganik, PhD Department of Sociology and Office of Population Research Princeton University, USA mjs3@princeton.edu

  2. Background • RDS estimates depend critically on respondents’ self-reported personal network size (degree) • Earlier studies have found that personal network size is often reported consistently (Marsden, 1990). Is this true for hidden populations? • We measure test-retest reliability taking advantage of the fact that many respondents visit the study site twice in RDS studies

  3. RDS studies in the Domincan Republic-2007 • Linked bio-behavioural surveillance conducted among FSWs, DUs and MSM in four cities in the Dominican Republic using RDS • Cities: Santo Domingo, Santiago, Barahona, Higuey • Eligible persons were 15 years +, lived in respective province in which study was conducted and met criteria respective to high risk behaviours • FSWs were females who exchanged sex for money in the previous six months • DUs were females or males who used illicit drugs in the previous three months • MSM were males who had anal or oral sexual relations with another man in the previous six months.

  4. Methods • We measure network size using 4 questions initially (time 1) and at follow-up (time 2) • How many (men, women or both) do you know and they know you that have (eligibility behavior)? • How many of them (repeat number above) live in this province? • How many of them (repeat number above)are 15 years or older? • How many of them (repeat number above)have you seen in the last week?

  5. Fig 1. Scatterplot of degree at time 1 and 2; Drug users in Santiago

  6. Fig 2. Spearman rank correlation of degreeat time 1 and 2; 12 sites

  7. Fig 3. Disease prevalence estimates using degree at time 1 and 2; Drug users, Santiago

  8. Fig 4. Difference in disease prevalence estimates for 12 cities (no missing degree data)

  9. Conclusion • Personal network size seems to have a low test-retest reliability among MSM, DU, and FSWs in the Dominican Republic • In some cases, this can lead to epidemiologically significantly different estimates of disease prevalence

  10. Some Questions • Are those that return for a secondary incentive different in some way? • Is this a useful method for testing behavioral questions? • Should we pull in network size outliers whenever we analyze RDS data? • How much variation in the estimates is too much (disease vs. behavioral estimates)?

  11. Recommendations • Further investigation needed on network size consistency • Further investigation needed on reliability of behavioral measurements • Further investigation needed on the impact of interviewer bias • Improved methods of structuring the network size question • Improved methods to probe for more accurate responses

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