A qualitative analysis of peer recruitment pressures in respondent driven sampling: Are risks above the ethical limit?

Integration of a geospatially targeted community-based testing approach with respondent-driven sampling to identify people who inject drugs living with HIV and HCV in Patti and Gorakhpur, India

BACKGROUND

Respondent-driven sampling (RDS), a network recruitment approach, is effective at reaching people who inject drugs (PWID), but other strategies may be needed to reach PWID at risk or living with HIV and/or Hepatitis C (HCV). We examined the impact of integrating geospatially targeted community-based HIV/HCV testing with an RDS survey.

METHODS

PWID were recruited between 2019 and 2021 in Patti and Gorakhpur, India, in a two-phased approach for identifying PWID living with HIV/HCV. Phase 1 was an RDS survey, in which participants reported injection venues. Venues with the highest prevalence of HIV/HCV viremia were selected for Phase 2: community-based testing. All participants underwent rapid HIV and HCV testing and viral load quantification. Using Pearson's chi-squared test, two-sided exact significance tests, and t-tests, we compared prevalence and identification rates for each of the primary outcomes: the number of PWID 1) living with HIV/HCV, 2) undiagnosed, and 3) viremic.

RESULTS

Both approaches identified large numbers of PWID (n∼500 each; N=2011) who were living with HIV/HCV and had transmission potential (i.e., detectable viremia). The community-based approach identified a higher proportion of individuals living with HCV (76.4% vs. 69.6% in Gorakhpur and 36.3% vs. 29.0% in Patti). Community-based testing was also faster at identifying PWID with detectable HIV viremia. Both approaches identified PWID with varying demographic characteristics.

CONCLUSIONS

Community-based testing was more efficient than RDS overall, but both may be required to reach PWID of varying characteristics. Surveillance should collect data on injection venues to facilitate community-based testing and maximize case identification.

In the name of science: Ethical violations in the ECHO randomised trial

It was in the 1990s, that the possibility of increased transmission of HIV with the use of injectable contraceptive Depo-Provera®, was first flagged in medical literature. This has posed a challenge for its use in countries, particularly in the African region, where the prevalence and transmission rate of HIV is high. In 2015, a randomised 'clinical' trial, the Evidence for Contraceptive Options and HIV Outcomes (ECHO) was launched in four African countries to resolve the question whether the increased risk was causal. Contrary to expectations, the ECHO trial successfully recruited and randomised the specified number of girls/women participants. This paper argues that this was made possible by exercising undue influence, by using incentives, coercive language, and by concealing the real nature of the clinical trial during recruitment. The ECHO trial is unique in subjecting a group of healthy girls/women knowingly to a contraceptive drug with an intention not of finding out whether it is efficacious as a contraceptive, but to find out how risky or life-threatening its use could be. Thus, the ECHO trial has violated one of the central tenets of the Helsinki Declaration by privileging pursuit of knowledge over the interests of the girl/women trial participants from Africa.

General regression methods for respondent-driven sampling data

Respondent-driven sampling is a variant of link-tracing sampling techniques that aim to recruit hard-to-reach populations by leveraging individuals’ social relationships. As such, a respondent-driven sample has a graphical component which represents a partially observed network of unknown structure. Moreover, it is common to observe homophily, or the tendency to form connections with individuals who share similar traits. Currently, there is a lack of principled guidance on multivariate modelling strategies for respondent-driven sampling to address peer effects driven by homophily and the dependence between observations within the network. In this work, we propose a methodology for general regression techniques using respondent-driven sampling data. This is used to study the socio-demographic predictors of HIV treatment optimism (about the value of antiretroviral therapy) among gay, bisexual and other men who have sex with men, recruited into a respondent-driven sampling study in Montreal, Canada.

Clustering of chronic hepatitis B screening intentions in social networks of Moroccan immigrants in the Netherlands

Background

Early detection, identification, and treatment of chronic hepatitis B through screening is vital for those at increased risk, e.g. born in hepatitis B endemic countries. In the Netherlands, Moroccan immigrants show low participation rates in health-related screening programmes. Since social networks influence health behaviour, we investigated whether similar screening intentions for chronic hepatitis B cluster within social networks of Moroccan immigrants.

Methods

We used respondent-driven sampling (RDS) where each participant (“recruiter”) was asked to complete a questionnaire and to recruit three Moroccans (“recruitees”) from their social network. Logistic regression analyses were used to analyse whether the recruiters’ intention to request a screening test was similar to the intention of their recruitees.

Results

We sampled 354 recruiter-recruitee pairs: for 154 pairs both participants had a positive screening intention, for 68 pairs both had a negative screening intention, and the remaining 132 pairs had a discordant intention to request a screening test. A tie between a recruiter and recruitee was associated with having the same screening intention, after correction for sociodemographic variables (OR 1.70 [1.15–2.51]).

Conclusions

The findings of our pilot study show clustering of screening intention among individuals in the same network. This provides opportunities for social network interventions to encourage participation in hepatitis B screening initiatives.

Intervention Reach and Sexual Risk Reduction of a Multi-level, Community-Based HIV Prevention Intervention for Crack Users in San Salvador, El Salvador

This article examines the effects of a multi-level, community-based HIV prevention intervention for crack users residing in low-income neighborhoods in San Salvador, El Salvador conducted between August 2011 and June 2016. The intervention consisted of three components introduced sequentially: (1) rapid HIV testing in community settings; (2) a social network HIV testing intervention; and (3) small group interventions with crack users who were members of the same social network. The intervention was evaluated with an interrupted time series design in which we used respondent-driven sampling to conduct 7 cross-sectional surveys with crack users along a 3-4 month period for each assessment (total n = 1597). Results revealed a significant increase in exposure to the intervention over time with 50% of the participants reporting exposure to one or more of the three components. Getting an HIV test at the community site was associated with reductions in total times each individual had sex without a condom (p < 0.05) compared to those who had been exposed to no intervention components. Being referred by another crack user through the Social Network HIV intervention was also associated with reductions in total numbers of condomless sex (p < 0.05) The cumulative effect of being exposed to more than one intervention component was associated with reductions in total number of times individuals had condomless sex (p < 0.05). In spite of the high level of intervention reach and that self-reported exposure to intervention components was associated with lower sexual risk, reductions in sexual risk over time were not observed in the full sample, indicating that the penetration of HIV prevention components was not sufficient to produce population level change.

Empirical evidence of recruitment bias in a network study of people who inject drugs

Background: Epidemiologic surveys of people who inject drugs (PWID) can be difficult to conduct because potential participants may fear exposure or legal repercussions. Respondent-driven sampling (RDS) is a procedure in which subjects recruit their eligible social contacts. The statistical validity of RDS surveys of PWID and other risk groups depends on subjects recruiting at random from among their network contacts. Objectives: We sought to develop and apply a rigorous definition and statistical tests for uniform network recruitment in an RDS survey. Methods: We undertook a detailed study of recruitment bias in a unique RDS study of PWID in Hartford, CT, the USA in which the network, individual-level covariates, and social link attributes were recorded. A total of n=527 participants (402 male, 123 female, and two individuals who did not specify their gender) within a network of 2626 PWID were recruited. Results: We found strong evidence of recruitment bias with respect to age, homelessness, and social relationship characteristics. In the discrete model, the estimated hazard ratios regarding the significant features of recruitment time and choice of recruitee were: alter's age 1.03 [1.02, 1.05], alter's crack-using status 0.70 [0.50, 1.00], homelessness difference 0.61 [0.43, 0.87], and sharing activities in drug preparation 2.82 [1.39, 5.72]. Under both the discrete and continuous-time recruitment regression models, we reject the null hypothesis of uniform recruitment. Conclusions: The results provide the evidence that for this study population of PWID, recruitment bias may significantly alter the sample composition, making results of RDS surveys less reliable. More broadly, RDS studies that fail to collect comprehensive network data may not be able to detect biased recruitment when it occurs.

Overlooked Threats to Respondent Driven Sampling Estimators: Peer Recruitment Reality, Degree Measures, and Random Selection Assumption

Intensive sociometric network data were collected from a typical respondent driven sample (RDS) of 528 people who inject drugs residing in Hartford, Connecticut in 2012-2013. This rich dataset enabled us to analyze a large number of unobserved network nodes and ties for the purpose of assessing common assumptions underlying RDS estimators. Results show that several assumptions central to RDS estimators, such as random selection, enrollment probability proportional to degree, and recruitment occurring over recruiter's network ties, were violated. These problems stem from an overly simplistic conceptualization of peer recruitment processes and dynamics. We found nearly half of participants were recruited via coupon redistribution on the street. Non-uniform patterns occurred in multiple recruitment stages related to both recruiter behavior (choosing and reaching alters, passing coupons, etc.) and recruit behavior (accepting/rejecting coupons, failing to enter study, passing coupons to others). Some factors associated with these patterns were also associated with HIV risk.

Identification of Homophily and Preferential Recruitment in Respondent-Driven Sampling

Respondent-driven sampling (RDS) is a link-tracing procedure used in epidemiologic research on hidden or hard-to-reach populations in which subjects recruit others via their social networks. Estimates from RDS studies may have poor statistical properties due to statistical dependence in sampled subjects' traits. Two distinct mechanisms account for dependence in an RDS study: homophily, the tendency for individuals to share social ties with others exhibiting similar characteristics, and preferential recruitment, in which recruiters do not recruit uniformly at random from their network alters. The different effects of network homophily and preferential recruitment in RDS studies have been a source of confusion and controversy in methodological and empirical research in epidemiology. In this work, we gave formal definitions of homophily and preferential recruitment and showed that neither is identified in typical RDS studies. We derived nonparametric identification regions for homophily and preferential recruitment and showed that these parameters were not identified unless the network took a degenerate form. The results indicated that claims of homophily or recruitment bias measured from empirical RDS studies may not be credible. We applied our identification results to a study involving both a network census and RDS on a population of injection drug users in Hartford, Connecticut (2012-2013).