This paper identifies an important paradigm shift in social research on HIV transmission, drug abuse, and risk reduction research. The article describes the key research trends and the institutional support for social network analysis in the HIV and drug risk field for the past decade. Key hypotheses and recommended areas for future research are identified.

Research regarding HIV transmission has been interested in the role of bridge groups, a venue for HIV transmission consisting of individuals grouped according to social roles that intersect at disparate populations, to which they may remain weakly linked. Bridge groups enable HIV transmission between separate types of risk groups, not simply between individuals, such as among gay men or among IDUs. For some time, researchers have speculated on the existence and function of bridge groups in the transmission of HIV between injection drug users to populations far removed from this targeted population. Despite various research efforts, we still know very little about such groups. Some research has surmised that gay male IDUs are a likely bridge group, as are male street prostitutes. This study examines bridge group members* perceptions of the realities of their social relations and HIV risk behaviors. The anecdotes that illustrate the functions of this bridge group are representative of all participants' stories. The core study participants are HIV-positive injection drug users who share needles with one another, but their links extend beyond drug use. All engage in risky, noncommercial sexual behaviors with one another and with individuals beyond the network. Some report that they engage in risky sexual behaviors with paying clients who are not part of the drug culture and who request these unsafe behaviors, often with the knowledge that the sex workers are seropositive. After a discussion of the findings, the manuscript discusses some bridge group characteristics to consider in future interventions and research, including rationales for avoiding safer sex practices, sexual segregation, and abuse histories.

In classic statistical theory, if a random sample is drawn from a population whose underlying distribution is known, it may be assumed that the properties of the sample mirror those of the population (Snedecor and Cochran, 1972). On that cornerstone is built a statistical superstructure that permits estimation, hypothesis testing, assurance of internal validity, generalizability, and modeling. For a variety of actual sampling schemes — simple random, stratified, probability proportional to size, systematic, cluster, multistage — considerable mathematical work has established appropriate point estimate and variance formulas, and has defined the potential for bias and other threats to validity (Levy and Lemeshow, 1980). This body of work provides satisfying precision for the estimation of uncertainty in defining population characteristics.