Assessing the Geographic Coverage and Spatial Clustering of Illicit Drug Users Recruited through Respondent-Driven Sampling in New York City

Abstract

We assess the geographic coverage and spatial clustering of drug users recruited through respondent-driven sampling (RDS) and discuss the potential for biased RDS prevalence estimates. Illicit drug users aged 18–40 were recruited through RDS (N = 401) and targeted street outreach (TSO) (N = 210) in New York City. Using the Google Maps API™, we calculated travel distances and times using public transportation between each participant’s recruitment location and the study office and between RDS recruiter–recruit pairs. We used K function analysis to evaluate and compare spatial clustering of (1) RDS vs. TSO respondents and (2) RDS seeds vs. RDS peer recruits. All participant recruitment locations clustered around the study office; however, RDS participants were significantly more likely to be recruited within walking distance of the study office than TSO participants. The TSO sample was also less spatially clustered than the RDS sample, which likely reflects (1) the van’s ability to increase the sample’s geographic heterogeneity and (2) that more TSO than RDS participants were enrolled on the van. Among RDS participants, individuals recruited spatially proximal peers, geographic coverage did not increase as recruitment waves progressed, and peer recruits were not less spatially clustered than seeds. Using a mobile van to recruit participants had a greater impact on the geographic coverage and spatial dependence of the TSO than the RDS sample. Future studies should consider and evaluate the impact of the recruitment approach on the geographic/spatial representativeness of the sample and how spatial biases, including the preferential recruitment of proximal peers, could impact the precision and accuracy of estimates.

Appendices

Appendix 1

TABLE 2 Theory, objective, hypotheses, analytic approach, and key findings in the evaluation of geographic coverage and spatial dependence of illicit drug users recruited through respondent-driven sampling, New York City

Appendix 2

FIG. 7

Convergence plot showing ${\widehat{p}}_1,\kern0.5em {\widehat{p}}_2,\kern0.5em \cdots, \kern0.5em {\widehat{p}}_n$ for self-reported HIV status in the TSO sample. The black solid line represents the cumulative estimate of the prevalence, and the red dotted line represents the estimate based on the complete sample, ${\widehat{p}}_n$. As seen in this figure, the prevalence of self-reported HIV in the TSO sample is relatively stable over time.

FIG. 8

Convergence plot showing ${\widehat{p}}_1,\kern0.5em {\widehat{p}}_2,\kern0.5em \cdots, \kern0.5em {\widehat{p}}_n$ for self-reported HIV status in the RDS sample. The black solid line represents the cumulative estimate of the prevalence, and the red dotted line represents the estimate based on the complete sample, ${\widehat{p}}_n$. As seen in this figure, the prevalence of self-reported HIV in the RDS sample is relatively stable over time.

FIG. 9

The bottleneck plot for self-reported HIV status shows the cumulative proportion of the RDS sample reporting HIV-positive status in New York City, by seed (N = 27). While there are 27 different seeds and consequently 27 different recruitment chains (of varying lengths), some are difficult to distinguish because the prevalence within that chain remains constant at 0 %. The red dotted line represents the estimate of self-reported HIV status based on the complete sample, ${\widehat{p}}_n$.

Appendix 3

FIG. 10

Distribution of days between recruiter’s baseline survey and recruit’s baseline survey. This figure displays the number of participants (y-axis) enrolled in the START study according to the number of days he/she enrolled after his/her recruiter (x-axis). Of note, 49 individuals (30 %) were enrolled in the study within 1 week of the person who recruited him/her (range 0–440 days ).

FIG. 11

Scatter plot for the correlation between a recruit’s travel distance to the study office (miles) and the number of days between the recruiter’s baseline survey and his/her recruit’s baseline survey (rho = 0.09864; P value = 0.2103).

FIG. 12

Scatter plot for the correlation between a recruit’s travel time to the study office (minutes) and the number of days between the recruiter’s baseline survey and his/her recruit’s baseline survey (rho = 0.06461; P value = 0.4126).

FIG. 13

Miles traveled by recruits to the study office. This figure displays the distance traveled by recruits to the office (miles) for those recruited more than a week after his/her recruiter (one_week=0) and for those recruited within a week (one_week = 1) of his/her recruiter. When categorized as 1 week or less vs. more than 1 week between recruiter’s baseline visit and recruit’s baseline visit, there was no significant difference in the distance (miles) traveled by the recruit to the study office (P value = 0.9555).

FIG. 14

Minutes traveled by recruits to the study office. This figure displays the time traveled by recruits to the office (minutes) for those recruited more than a week after his/her recruiter (one_week=0) and for those recruited within a week (one_week = 1) of his/her recruiter. When categorized as 1 week or less vs. more than 1 week between recruiter’s baseline visit and recruit’s baseline visit, there was no significant difference in the time (minutes) traveled by the recruit to the study office (P value = 0.8475).

FIG. 15

Scatter plot for the correlation between recruiter’s distance (miles) to the office and days between recruiter’s baseline survey and recruit’s baseline survey (rho = −0.02042; P value = 0.7959).

FIG. 16

Scatter plot for the correlation between recruiter’s time (minutes) to the office and days between recruiter’s baseline survey and recruit’s baseline survey (rho = −0.03607; P value = 0.6476).

FIG. 17

Miles traveled by recruiters to the study office. This figure displays the distance (miles) traveled by recruiters to the office for those who’s recruits enrolled in the study more than a week after him/her (one_week=0) and for those who’s recruits enrolled in the study within a week (one_week = 1) of him/her. When categorized as 1 week or less vs. more than 1 week between recruiter’s baseline visit and recruit’s baseline visit, there was no significant difference in the distance traveled (miles) by the recruiter to the study office (P value = 0.1844).

FIG. 18

Minutes traveled by recruiters to the study office. The above figure displays the time (minutes) traveled by recruiters to the office for those who’s recruits enrolled in the study more than a week after him/her (one_week=0) and for those who’s recruits enrolled in the study within a week (one_week = 1) of him/her. When categorized as 1 week or less vs. more than 1 week between recruiter’s baseline visit and recruit’s baseline visit, there was no significant difference in the time traveled (minutes) by the recruiter to the study office (P value = 0.1930).