Evaluation of the role of location and distance in recruitment in respondent-driven sampling

Reassessing geographic bottlenecks in a respondent-driven sampling based multicity study in Brazil

This study analyzes the spatial dynamics of drug users' recruitment chains in the context of a respondent-driven sampling (RDS) study in the city of Recife, Brazil. The purpose is to understand the geographic bottlenecks, influenced by social geography, which have been a major challenge for RDS-based studies. Temporo-spatial analysis was used. Sequential maps depicted the dynamics of the recruiting process, considering neighborhood of residence and/or places of drug use. Poisson regression was fitted to model the recruiting rate by neighborhood of residence and/or places of drug use, and the different neighborhoods' demographics. The distance between neighborhood of residence and/or places of drug use and the assessment center was negatively associated with recruitment. There was a positive association between the proportion of the population living in informal settings and the recruiting rate per neighborhood of residence and/or places of drug use. Recruitment chains depend on the social geography and demographics of the population. Studies should incorporate seeds from as many neighborhoods as possible, and more than one assessment center should be utilized.

Network-Based Research on Rural Opioid Use: an Overview of Methods and Lessons Learned

PURPOSE OF REVIEW

The purpose of this paper is to provide a thorough overview of methods used for recruitment, network data collection, and network data management in a network-based study of rural people who use drugs (PWUD) and to offer methodological recommendations for future research on rural drug use.

RECENT FINDINGS

The Social Networks among Appalachian People (SNAP) study recruited a cohort of 503 rural PWUD via respondent-driven sampling (RDS) and has retained more than 80% of eligible participants over 7-9 years. SNAP has yielded important methodological insights, including that (1) RDS referral was non-random and disproportionately involved kin and (2) interviewer-administered questionnaires were successful in eliciting accurate name and age information about network members. The SNAP experience suggests that RDS was a successful recruitment strategy for rural PWUD and questionnaires administered by community-based interviewers in the context of a Certificate of Confidentiality could elicit detailed data on PWUD risk networks.

Opportunities for Enhanced Strategic Use of Surveys, Medical Records, and Program Data for HIV Surveillance of Key Populations: Scoping Review

BACKGROUND

Normative guidelines from the World Health Organization recommend tracking strategic information indicators among key populations. Monitoring progress in the global response to the HIV epidemic uses indicators put forward by the Joint United Nations Programme on HIV/AIDS. These include the 90-90-90 targets that require a realignment of surveillance data, routinely collected program data, and medical record data, which historically have developed separately.

OBJECTIVE

The aim of this study was to describe current challenges for monitoring HIV-related strategic information indicators among key populations ((men who have sex with men [MSM], people in prisons and other closed settings, people who inject drugs, sex workers, and transgender people) and identify future opportunities to enhance the use of surveillance data, programmatic data, and medical record data to describe the HIV epidemic among key populations and measure the coverage of HIV prevention, care, and treatment programs.

METHODS

To provide a historical perspective, we completed a scoping review of the expansion of HIV surveillance among key populations over the past three decades. To describe current efforts, we conducted a review of the literature to identify published examples of SI indicator estimates among key populations. To describe anticipated challenges and future opportunities to improve measurement of strategic information indicators, particularly from routine program and health data, we consulted participants of the Third Global HIV Surveillance Meeting in Bangkok, where the 2015 World Health Organization strategic information guidelines were launched.

RESULTS

There remains suboptimal alignment of surveillance and programmatic data, as well as routinely collected medical records to facilitate the reporting of the 90-90-90 indicators for HIV among key populations. Studies (n=3) with estimates of all three 90-90-90 indicators rely on cross-sectional survey data. Programmatic data and medical record data continue to be insufficiently robust to provide estimates of the 90-90-90 targets for key populations.

CONCLUSIONS

Current reliance on more active data collection processes, including key population-specific surveys, remains warranted until the quality and validity of passively collected routine program and medical record data for key populations is optimized.

One-step estimation of networked population size: Respondent-driven capture-recapture with anonymity

Size estimation is particularly important for populations whose members experience disproportionate health issues or pose elevated health risks to the ambient social structures in which they are embedded. Efforts to derive size estimates are often frustrated when the population is hidden or hard-to-reach in ways that preclude conventional survey strategies, as is the case when social stigma is associated with group membership or when group members are involved in illegal activities. This paper extends prior research on the problem of network population size estimation, building on established survey/sampling methodologies commonly used with hard-to-reach groups. Three novel one-step, network-based population size estimators are presented, for use in the context of uniform random sampling, respondent-driven sampling, and when networks exhibit significant clustering effects. We give provably sufficient conditions for the consistency of these estimators in large configuration networks. Simulation experiments across a wide range of synthetic network topologies validate the performance of the estimators, which also perform well on a real-world location-based social networking data set with significant clustering. Finally, the proposed schemes are extended to allow them to be used in settings where participant anonymity is required. Systematic experiments show favorable tradeoffs between anonymity guarantees and estimator performance. Taken together, we demonstrate that reasonable population size estimates are derived from anonymous respondent driven samples of 250-750 individuals, within ambient populations of 5,000-40,000. The method thus represents a novel and cost-effective means for health planners and those agencies concerned with health and disease surveillance to estimate the size of hidden populations. We discuss limitations and future work in the concluding section.

Social networks, migration, and HIV testing among Latinos in a new immigrant destination: Insights from a qualitative study

Latinos in the U.S. are disproportionately affected by HIV and are more likely than non-Latinos to present with a late diagnosis, which delays engagement in HIV care and treatment. Social networks may provide normative influence and social support for HIV testing, but a contextualised understanding of networks is needed in order to maximise these social resources. We conducted qualitative interviews with foreign-born Latino men and transgender women (n = 17) in a new immigrant destination to explore their social networks. Most participants described having smaller social networks after migrating. Networks included both local and transnational ties, but most participants had few close ties. Contextual factors including stigma and geographic dispersion limited the re-construction of networks with close ties after migration. HIV testing was not a common topic of discussion with social network ties. Efforts to improve early uptake of HIV testing among Latino immigrants may benefit from engaging with social networks, but such efforts need to address how the context in which networks operate enables access to testing.

Surveillance and response for high-risk populations: what can malaria elimination programmes learn from the experience of HIV?

To eliminate malaria, malaria programmes need to develop new strategies for surveillance and response appropriate for the changing epidemiology that accompanies transmission decline, in which transmission is increasingly driven by population subgroups whose behaviours place them at increased exposure. Conventional tools of malaria surveillance and response are likely not sufficient in many elimination settings for accessing high-risk population subgroups, such as mobile and migrant populations (MMPs), given their greater likelihood of asymptomatic infections, illegal risk behaviours, limited access to public health facilities, and high mobility including extended periods travelling away from home. More adaptive, targeted strategies are needed to monitor transmission and intervention coverage effectively in these groups. Much can be learned from HIV programmes’ experience with “second generation surveillance”, including how to rapidly adapt surveillance and response strategies to changing transmission patterns, biological and behavioural surveys that utilize targeted sampling methods for specific behavioural subgroups, and methods for population size estimation. This paper reviews the strategies employed effectively for HIV programmes and offers considerations and recommendations for adapting them to the malaria elimination context.

Update on respondent-driven sampling: Theory and practical considerations for studies of persons who inject drugs

In the last 5 years, more than 600 articles using respondent-driven sampling has been published. This article aims to provide an overview of this sampling technique with an update on the key questions that remain when using respondent-driven sampling, with regard to its application and estimators. Respondent-driven sampling was developed by Heckathorn in 1997 and was based on the principle of individuals recruiting other individuals, who themselves were recruited in previous waves. When there is no sampling frame, respondent-driven sampling has demonstrated its ability to capture individuals belonging to “hidden” or “hard-to-reach” populations in numerous epidemiological surveys. People who use drugs, sex workers, or men who have sex with men are notable examples of specific populations studied using this technique, particularly by public agencies such as the Centers for Disease Control and Prevention in the United States. Respondent-driven sampling, like many others, is based on a set of assumptions that, when respected, can ensure an unbiased estimator. Based on a literature review, we will discuss, among other topics, the effect of violating these assumptions. A special focus is made on surveys of persons who inject drugs. Publications show two major thrusts—methodological and applied researches—for providing practical recommendations in conducting respondent-driven sampling studies. The reasons why respondent-driven sampling did not work for a given population of interest will usually provide important insights for designing health-promoting interventions for that population.

HIV Prevalence Among People Who Inject Drugs in Greater Kuala Lumpur Recruited Using Respondent-Driven Sampling

The HIV epidemic in Malaysia is concentrated among people who inject drugs (PWID). Accurate estimates of HIV prevalence are critical for developing appropriate treatment and prevention interventions for PWID in Malaysia. In 2010, 461 PWID were recruited using respondent-driven sampling in Greater Kuala Lumpur, Malaysia. Participants completed rapid HIV testing and behavioral assessments. Estimates of HIV prevalence were computed for each of the three recruitment sites and the overall sample. HIV prevalence was 15.8 % (95 % CI 12.5-19.2 %) overall but varied widely by location: 37.0 % (28.6-45.4 %) in Kampung Baru, 10.3 % (5.0-15.6 %) in Kajang, and 6.3 % (3.0-9.5 %) in Shah Alam. Recruitment extended to locations far from initial interview sites but was concentrated around discrete geographic regions. We document the high prevalence of HIV among PWID in Greater Kuala Lumpur. Sustained support for community surveillance and HIV prevention interventions is needed to stem the HIV epidemic among PWID in Malaysia.

Assessing the geographic coverage and spatial clustering of illicit drug users recruited through respondent-driven sampling in New York City

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.

Evaluation of respondent-driven sampling in a study of urban young men who have sex with men

Evidence suggests that respondent-driven sampling (RDS) is an efficient approach to sampling among varied populations of adult men who have sex with men (MSM) both in the USA and abroad, although no studies have yet evaluated its performance among younger MSM, a population with a steep rise in HIV infection in recent years. Young MSM (YMSM) may differ in terms of their connectedness to other YMSM (e.g., due to evolving sexual identity, internalization of sexual minority stigma, and lack of disclosure to others) and mobility (e.g., due to parental monitoring) which may inhibit the sampling process. The aims of this study were to evaluate the efficiency and effectiveness of RDS-based sampling among young urban MSM and to identify factors associated with recruitment success. We hypothesized that demographic, social, behavioral, and network factors, including racial/ethnic minority status, homelessness (i.e., as an indicator of socioeconomic marginalization), HIV-positive status, substance use problems, gay community connectedness, and network size would be positively related to recruitment productivity, while sexual minority stigmatization, environmental barriers (e.g., parental monitoring), and meeting sex partners on the internet (i.e., virtual venue) would be negatively related to recruitment productivity. Between December 2009 and February 2013, we used RDS to recruit a sample of 450 YMSM, ages 16-20. Findings suggest that the use of RDS for sampling among YMSM is challenging and may not be feasible based on the slow pace of recruitment and low recruitment productivity. A large number of seeds (38 % of the sample, n = 172) had to be added to the sample to maintain a reasonable pace of recruitment, which makes use of the sample for RDS-based population estimates questionable. In addition, the prevalence of short recruitment chains and segmentation in patterns of recruitment by race/ethnicity further hamper the network recruitment process. Thus, RDS was not particularly efficient in terms of the rate of recruitment or effective in generating a representative sample. Hypotheses regarding factors associated with recruitment success were supported for network size and internalized stigma (but not other factors), suggesting that participants with larger network sizes or high levels of internalized stigma may have more and less success recruiting others, respectively.

Evaluating outcome-correlated recruitment and geographic recruitment bias in a respondent-driven sample of people who inject drugs in Tijuana, Mexico

Respondent-driven sampling's (RDS) widespread use and reliance on untested assumptions suggests a need for new exploratory/diagnostic tests. We assessed geographic recruitment bias and outcome-correlated recruitment among 1,048 RDS-recruited people who inject drugs (Tijuana, Mexico). Surveys gathered demographics, drug/sex behaviors, activity locations, and recruiter-recruit pairs. Simulations assessed geographic and network clustering of active syphilis (RPR titers ≥1:8). Gender-specific predicted probabilities were estimated using logistic regression with GEE and robust standard errors. Active syphilis prevalence was 7 % (crude: men = 5.7 % and women = 16.6 %; RDS-adjusted: men = 6.7 % and women = 7.6 %). Syphilis clustered in the Zona Norte, a neighborhood known for drug and sex markets. Network simulations revealed geographic recruitment bias and non-random recruitment by syphilis status. Gender-specific prevalence estimates accounting for clustering were highest among those living/working/injecting/buying drugs in the Zona Norte and directly/indirectly connected to syphilis cases (men: 15.9 %, women: 25.6 %) and lowest among those with neither exposure (men: 3.0 %, women: 6.1 %). Future RDS analyses should assess/account for network and spatial dependencies.

Sampling methodologies for epidemiologic surveillance of men who have sex with men and transgender women in Latin America: an empiric comparison of convenience sampling, time space sampling, and respondent driven sampling

Alternatives to convenience sampling (CS) are needed for HIV/STI surveillance of most-at-risk populations in Latin America. We compared CS, time space sampling (TSS), and respondent driven sampling (RDS) for recruitment of men who have sex with men (MSM) and transgender women (TW) in Lima, Peru. During concurrent 60-day periods from June-August, 2011, we recruited MSM/TW for epidemiologic surveillance using CS, TSS, and RDS. A total of 748 participants were recruited through CS, 233 through TSS, and 127 through RDS. The TSS sample included the largest proportion of TW (30.7 %) and the lowest percentage of subjects who had previously participated in HIV/STI research (14.9 %). The prevalence of newly diagnosed HIV infection, according to participants' self-reported previous HIV diagnosis, was highest among TSS recruits (17.9 %) compared with RDS (12.6 %) and CS (10.2 %). TSS identified diverse populations of MSM/TW with higher prevalences of HIV/STIs not accessed by other methods.

Respondent-driven sampling for an adolescent health study in vulnerable urban settings: a multi-country study

The global adolescent population is larger than ever before and is rapidly urbanizing. Global surveillance systems to monitor youth health typically use household- and school-based recruitment methods. These systems risk not reaching the most marginalized youth made vulnerable by conditions of migration, civil conflict, and other forms of individual and structural vulnerability. We describe the methodology of the Well-Being of Adolescents in Vulnerable Environments survey, which used respondent-driven sampling (RDS) to recruit male and female youth aged 15-19 years and living in economically distressed urban settings in Baltimore, MD; Johannesburg, South Africa; Ibadan, Nigeria; New Delhi, India; and Shanghai, China (migrant youth only) for a cross-sectional study. We describe a shared recruitment and survey administration protocol across the five sites, present recruitment parameters, and illustrate challenges and necessary adaptations for use of RDS with youth in disadvantaged urban settings. We describe the reach of RDS into populations of youth who may be missed by traditional household- and school-based sampling. Across all sites, an estimated 9.6% were unstably housed; among those enrolled in school, absenteeism was pervasive with 29% having missed over 6 days of school in the past month. Overall findings confirm the feasibility, efficiency, and utility of RDS in quickly reaching diverse samples of youth, including those both in and out of school and those unstably housed, and provide direction for optimizing RDS methods with this population. In our rapidly urbanizing global landscape with an unprecedented youth population, RDS may serve as a valuable tool in complementing existing household- and school-based methods for health-related surveillance that can guide policy.

Spatial recruitment bias in respondent-driven sampling: Implications for HIV prevalence estimation in urban heterosexuals

Respondent-driven sampling (RDS) is a study design used to investigate populations for which a probabilistic sampling frame cannot be efficiently generated. Biases in parameter estimates may result from systematic non-random recruitment within social networks by geography. We investigate the spatial distribution of RDS recruits relative to an inferred social network among heterosexual adults in New York City in 2010. Mean distances between recruitment dyads are compared to those of network dyads to quantify bias. Spatial regression models are then used to assess the impact of spatial structure on risk and prevalence outcomes. In our primary distance metric, network dyads were an average of 1.34 (95 % CI 0.82–1.86) miles farther dispersed than recruitment dyads, suggesting spatial bias. However, there was no evidence that demographic associations with HIV risk or prevalence were spatially confounded. Therefore, while the spatial structure of recruitment may be biased in heterogeneous urban settings, the impact of this bias on estimates of outcome measures appears minimal.

Respondent driven sampling is an effective method for engaging methamphetamine users in HIV prevention research in South Africa

BACKGROUND

South Africa, in the midst of the world's largest HIV epidemic, has a growing methamphetamine problem. Respondent driven sampling (RDS) is a useful tool for recruiting hard-to-reach populations in HIV prevention research, but its use with methamphetamine smokers in South Africa has not been described. This study examined the effectiveness of RDS as a method for engaging methamphetamine users in a Cape Town township into HIV behavioral research.

METHODS

Standard RDS procedures were used to recruit active methamphetamine smokers from a racially diverse peri-urban township in Cape Town. Effectiveness of RDS was determined by examining social network characteristics (network size, homophily, and equilibrium) of recruited participants.

RESULTS

Beginning with eight seeds, 345 methamphetamine users were enrolled over 6 months, with a coupon return rate of 67%. The sample included 197 men and 148 women who were racially diverse (73% Coloured, 27% Black African) and had a mean age of 28.8 years (SD=7.2). Social networks were adequate (mean network size >5) and mainly comprised of close social ties. Equilibrium on race was reached after 11 waves of recruitment, and after ≤3 waves for all other variables of interest. There was little to moderate preference for either in- or out-group recruiting in all subgroups.

CONCLUSIONS

Results suggest that RDS is an effective method for engaging methamphetamine users into HIV prevention research in South Africa. Additionally, RDS may be a useful strategy for seeking high-risk methamphetamine users for HIV testing and linkage to HIV care in this and other low resource settings.

Spatial, temporal and relational patterns in respondent-driven sampling: evidence from a social network study of rural drug users

BACKGROUND

Respondent-driven sampling (RDS) has become a common tool for recruiting high-risk populations for HIV research. However, few studies have explored the influence of geospatial proximity and relationship-level characteristics on RDS recruitment, particularly among high-risk individuals residing in rural areas of the US.

METHODS

In a social network study of 503 drug users in rural Central Appalachia, interviewer-administered questionnaires were used to collect relationship-level data (eg, duration of relationship, frequency of communication, kinship, social/financial support, trust, drug use and sex) and residential location. Demographic and drug-use similarity were also evaluated. Residential data were geocoded and road distance (km) between participants and (1) their network members and (2) the study site were computed. Seasonal patterns were assessed using node-level analysis, and dyadic analyses were conducted using generalised linear mixed models. Adjusted ORs (AORs) and 95% CIs are reported.

RESULTS

Differences in distance to the study office by season and order of study entry were not observed (F=1.49, p=0.209 and β=0.074, p=0.050, respectively). Participants with transportation lived significantly further from the interview site than their counterparts (p<0.001). Dyadic analyses revealed no association between RDS recruitment likelihood and geographic proximity. However, kinship (AOR 1.62; CI 1.02 to 2.58) and frequency of communication (AOR 1.63; CI 1.25 to 2.13) were significantly associated with RDS recruitment.

CONCLUSIONS

In this sample, recruitment from one's network was likely non-random, contradicting a core RDS assumption. These data underscore the importance of formative research to elucidate potential recruitment preferences and of quantifying recruitment preferences for use in analysis.

Substance abuse treatment utilization, HIV risk behaviors, and recruitment among suburban injection drug users in Long Island, New York

Prevention and treatment of injection drug use remains a public health concern. We used data from the 2005 Centers for Disease Control and prevention National HIV Behavioral Surveillance system to assess substance abuse treatment utilization, risk behaviors, and recruitment processes in a respondent driven sample of suburban injectors. Twelve service utilization and injection risk variables were analyzed using latent class analysis. Three latent classes were identified: low use, low risk; low use, high risk; and high use, moderate/high risk. In multivariate analysis, annual income <$15,000 (adjusted odds ratio (aOR) = 8.19 [95 % confidence interval (CI), 3.83-17.51]) and self-reported hepatitis C virus infection (aOR = 4.32, 95 % CI (1.84-10.17)) were significantly associated with class membership. Homophily, a measure of preferential recruitment showed that injectors with recent treatment utilization appear a more cohesive group than out-of-treatment injectors. Preferentially reaching injection drug users with high risk behaviors and no recent drug treatment history via respondent driven sampling will require future research.

Online respondent-driven sampling for studying contact patterns relevant for the spread of close-contact pathogens: a pilot study in Thailand

Background

Information on social interactions is needed to understand the spread of airborne infections through a population. Previous studies mostly collected egocentric information of independent respondents with self-reported information about contacts. Respondent-driven sampling (RDS) is a sampling technique allowing respondents to recruit contacts from their social network. We explored the feasibility of webRDS for studying contact patterns relevant for the spread of respiratory pathogens.

Materials and Methods

We developed a webRDS system for facilitating and tracking recruitment by Facebook and email. One-day diary surveys were conducted by applying webRDS among a convenience sample of Thai students. Students were asked to record numbers of contacts at different settings and self-reported influenza-like-illness symptoms, and to recruit four contacts whom they had met in the previous week. Contacts were asked to do the same to create a network tree of socially connected individuals. Correlations between linked individuals were analysed to investigate assortativity within networks.

Results

We reached up to 6 waves of contacts of initial respondents, using only non-material incentives. Forty-four (23.0%) of the initially approached students recruited one or more contacts. In total 257 persons participated, of which 168 (65.4%) were recruited by others. Facebook was the most popular recruitment option (45.1%). Strong assortative mixing was seen by age, gender and education, indicating a tendency of respondents to connect to contacts with similar characteristics. Random mixing was seen by reported number of daily contacts.

Conclusions

Despite methodological challenges (e.g. clustering among respondents and their contacts), applying RDS provides new insights in mixing patterns relevant for close-contact infections in real-world networks. Such information increases our knowledge of the transmission of respiratory infections within populations and can be used to improve existing modelling approaches. It is worthwhile to further develop and explore webRDS for the detection of clusters of respiratory symptoms in social networks.

Respondent driven sampling: determinants of recruitment and a method to improve point estimation

Introduction

Respondent-driven sampling (RDS) is a variant of a link-tracing design intended for generating unbiased estimates of the composition of hidden populations that typically involves giving participants several coupons to recruit their peers into the study. RDS may generate biased estimates if coupons are distributed non-randomly or if potential recruits present for interview non-randomly. We explore if biases detected in an RDS study were due to either of these mechanisms, and propose and apply weights to reduce bias due to non-random presentation for interview.

Methods

Using data from the total population, and the population to whom recruiters offered their coupons, we explored how age and socioeconomic status were associated with being offered a coupon, and, if offered a coupon, with presenting for interview. Population proportions were estimated by weighting by the assumed inverse probabilities of being offered a coupon (as in existing RDS methods), and also of presentation for interview if offered a coupon by age and socioeconomic status group.

Results

Younger men were under-recruited primarily because they were less likely to be offered coupons. The under-recruitment of higher socioeconomic status men was due in part to them being less likely to present for interview. Consistent with these findings, weighting for non-random presentation for interview by age and socioeconomic status group greatly improved the estimate of the proportion of men in the lowest socioeconomic group, reducing the root-mean-squared error of RDS estimates of socioeconomic status by 38%, but had little effect on estimates for age. The weighting also improved estimates for tribe and religion (reducing root-mean-squared-errors by 19–29%), but had little effect for sexual activity or HIV status.

Conclusions

Data collected from recruiters on the characteristics of men to whom they offered coupons may be used to reduce bias in RDS studies. Further evaluation of this new method is required.

Effectiveness of respondent driven sampling to recruit undocumented Central American immigrant women in Houston, Texas for an HIV behavioral survey

Respondent driven sampling (RDS) is widely used for HIV behavioral research among sex workers, drug users, and other hidden populations, but has had limited application in immigrant populations in the U.S. In 2010, we used RDS to recruit undocumented Central American immigrant women in Houston, Texas for an HIV behavioral survey. Beginning with three initial participants we recruited 226 women within 16 weeks. Social networks were dense and participants adopted the recruitment system with reasonable ease. Homophily scores indicated moderate within-group preference by country of origin. However, cross-group recruitment was sufficient to achieve a diverse sample that attained equilibrium for all demographic and sexual behavior characteristics. Overall, RDS was easy to implement, attained a large sample in a relatively short period of time, and reached an otherwise hidden population. Our results suggest that RDS is an effective method for recruiting undocumented Latina immigrants for HIV behavioral surveys.

The general population cohort in rural south-western Uganda: a platform for communicable and non-communicable disease studies

The General Population Cohort (GPC) was set up in 1989 to examine trends in HIV prevalence and incidence, and their determinants in rural south-western Uganda. Recently, the research questions have included the epidemiology and genetics of communicable and non-communicable diseases (NCDs) to address the limited data on the burden and risk factors for NCDs in sub-Saharan Africa. The cohort comprises all residents (52% aged ≥13years, men and women in equal proportions) within one-half of a rural sub-county, residing in scattered houses, and largely farmers of three major ethnic groups. Data collected through annual surveys include; mapping for spatial analysis and participant location; census for individual socio-demographic and household socioeconomic status assessment; and a medical survey for health, lifestyle and biophysical and blood measurements to ascertain disease outcomes and risk factors for selected participants. This cohort offers a rich platform to investigate the interplay between communicable diseases and NCDs. There is robust infrastructure for data management, sample processing and storage, and diverse expertise in epidemiology, social and basic sciences. For any data access enquiries you may contact the director, MRC/UVRI, Uganda Research Unit on AIDS by email to mrc@mrcuganda.org or the corresponding author.

Evaluation of respondent-driven sampling

BACKGROUND

Respondent-driven sampling is a novel variant of link-tracing sampling for estimating the characteristics of hard-to-reach groups, such as HIV prevalence in sex workers. Despite its use by leading health organizations, the performance of this method in realistic situations is still largely unknown. We evaluated respondent-driven sampling by comparing estimates from a respondent-driven sampling survey with total population data.

METHODS

Total population data on age, tribe, religion, socioeconomic status, sexual activity, and HIV status were available on a population of 2402 male household heads from an open cohort in rural Uganda. A respondent-driven sampling (RDS) survey was carried out in this population, using current methods of sampling (RDS sample) and statistical inference (RDS estimates). Analyses were carried out for the full RDS sample and then repeated for the first 250 recruits (small sample).

RESULTS

We recruited 927 household heads. Full and small RDS samples were largely representative of the total population, but both samples underrepresented men who were younger, of higher socioeconomic status, and with unknown sexual activity and HIV status. Respondent-driven sampling statistical inference methods failed to reduce these biases. Only 31%-37% (depending on method and sample size) of RDS estimates were closer to the true population proportions than the RDS sample proportions. Only 50%-74% of respondent-driven sampling bootstrap 95% confidence intervals included the population proportion.

CONCLUSIONS

Respondent-driven sampling produced a generally representative sample of this well-connected nonhidden population. However, current respondent-driven sampling inference methods failed to reduce bias when it occurred. Whether the data required to remove bias and measure precision can be collected in a respondent-driven sampling survey is unresolved. Respondent-driven sampling should be regarded as a (potentially superior) form of convenience sampling method, and caution is required when interpreting findings based on the sampling method.