African American men who have sex with men (MSM) are disproportionately affected by HIV and constitute more than half of all HIV-infected MSM in the USA.
Data from the New York City location of a multi-site study were used to evaluate the effectiveness of three HIV testing strategies for detecting previously undiagnosed, 18 to 64-year-old African American MSM. Effectiveness was defined as the identification of seropositive individuals.
Using a quasi-experimental design (N = 558), we examined HIV-positive test results for men tested via alternative venue testing, the social networks strategy, and partner counseling and referral services, as well as behavioral risk factors for 509 men tested through alternative venue testing and the social networks strategy.
Detection rates of HIV-positives were: alternative venue testing-6.3%, the social networks strategy-19.3%, and partner services-14.3%. The odds for detection of HIV-positive MSM were 3.6 times greater for the social networks strategy and 2.5 times greater for partner services than alternative venue testing. Men tested through alternative venue testing were younger and more likely to be gay-identified than men tested through the social networks strategy. Men who tested through the social networks strategy reported more sexual risk behaviors than men tested through alternative venue testing.
Findings suggest differential effectiveness of testing strategies. Given differences in the individuals accessing testing across strategies, a multi-strategic testing approach may be needed to most fully identify undiagnosed HIV-positive African American MSM.
"The use of different sampling methods (e.g. RDS vs. time-location sampling), either done within the same area at the same time [10-12], or, less informatively, at different times and/or places [13-15], clearly demonstrate that distinct subgroups within a broader population exist and are preferentially accessed by one method over another. "
[Show abstract][Hide abstract] ABSTRACT: Respondent driven sampling (RDS) was designed for sampling "hidden" populations and intended as a means of generating unbiased population estimates. Its widespread use has been accompanied by increasing scrutiny as researchers attempt to understand the extent to which the population estimates produced by RDS are, in fact, generalizable to the actual population of interest. In this study we compare two different methods of seed selection to determine whether this may influence recruitment and RDS measures.
Two seed groups were established. One group was selected as per a standard RDS approach of study staff purposefully selecting a small number of individuals to initiate recruitment chains. The second group consisted of individuals self-presenting to study staff during the time of data collection. Recruitment was allowed to unfold from each group and RDS estimates were compared between the groups. A comparison of variables associated with HIV was also completed.
Three analytic groups were used for the majority of the analyses--RDS recruits originating from study staff-selected seeds (n = 196); self-presenting seeds (n = 118); and recruits of self-presenting seeds (n = 264). Multinomial logistic regression demonstrated significant differences between the three groups across six of ten sociodemographic and risk behaviours examined. Examination of homophily values also revealed differences in recruitment from the two seed groups (e.g. in one arm of the study sex workers and solvent users tended not to recruit others like themselves, while the opposite was true in the second arm of the study). RDS estimates of population proportions were also different between the two recruitment arms; in some cases corresponding confidence intervals between the two recruitment arms did not overlap. Further differences were revealed when comparisons of HIV prevalence were carried out.
RDS is a cost-effective tool for data collection, however, seed selection has the potential to influence which subgroups within a population are accessed. Our findings indicate that using multiple methods for seed selection may improve access to hidden populations. Our results further highlight the need for a greater understanding of RDS to ensure appropriate, accurate and representative estimates of a population can be obtained from an RDS sample.
BMC Medical Research Methodology 07/2013; 13(1):93. DOI:10.1186/1471-2288-13-93 · 2.27 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The HIV/AIDS epidemic in the United States continues despite several recent noteworthy advances in HIV prevention. Contemporary approaches to HIV prevention involve implementing combinations of biomedical, behavioral, and structural interventions in novel ways to achieve high levels of impact on the epidemic. Methods are needed to develop optimal combinations of approaches for improving efficiency, effectiveness, and scalability. This article argues that operational research offers promise as a valuable tool for addressing these issues. We define operational research relative to domestic HIV prevention, identify and illustrate how operational research can improve HIV prevention, and pose a series of questions to guide future operational research. Operational research can help achieve national HIV prevention goals of reducing new infections, improving access to care and optimization of health outcomes of people living with HIV, and reducing HIV-related health disparities.
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