Presentation on theme: "Networks and interventions Acknowledgements USA National Institute on Drug Abuse Social Factors and HIV Risk (R01 DA06723) Drug use and HIV risk among."— Presentation transcript:
Networks and interventions Acknowledgements USA National Institute on Drug Abuse Social Factors and HIV Risk (R01 DA06723) Drug use and HIV risk among youth (R01 DA10411 ) Networks, norms and HIV risk among youth (R01 DA13128) USA National Institute on Mental Health Local context, social-control action, and HIV risk (R01 MH62280) Hundreds of Bushwick residents and others who participated in these studies Many collaborators and co-authors
Social Networks and HIV: Introduction of some concepts 1.Risk networks, social networks, and the spread of HIV and of social influence 2.Network-based interpretations of intervention models
Most HIV epidemiology, prevention, and policy has focused on individual knowledge, attitudes, personality and behaviors:
People also have social and behavioral ties of various types and strengths
Risk network ties can carry infections: Within relationships To or from an individual Throughout a community or small group
The concepts of network components and cores Two components; Seidman K-2 core is in red
Research has shown that network location affects probabilities of infection Thus, the probability that an infected person who engages in risky behavior will do so with an uninfected partner depends on their network locations. As does the probability that an uninfected person who engages in risky behavior will do so with an infectious person Cores and other microstructures of dense risk interaction are associated with higher seroprevalence
These thoughts lead to the following insight: HIV incidence is a socially-conditioned probability It depends on: Risk behavior Between at least two people, one of whom is uninfected and another of whom is infectious The susceptibility of the uninfected person (and thus, e.g., on STDs, which are unevenly distributed in networks and society) The infectiousness of the infected (and thus, on time since infection, on HAART use, and on STDs, which are all unevenly distributed in networks and society) For a given uninfected person, the probability that a partner is infected depends on the partners’ place in community networks –Friedman SR, Jose B, Neaigus A, Goldstein M, Mota P, Curtis R, Ildefonso G, Des Jarlais DC. Multiple Racial/Ethnic Subordination and HIV among Drug Injectors. In: M Singer (Ed.), The Political Economy of AIDS. Amityville, New York: Baywood Press, 1998. pp. 105-127. –Friedman SR, Jose B, Neaigus A, Curtis R, Vermund SH, Des Jarlais DC. (2000). Network-related mechanisms may help explain long-term HIV-1-seroprevalence levels that remain high but do not approach population-group saturation. American Journal of Epidemiology, 152 (10), 913-922.
Risk is a conditional probability +, on HAART Negative Unknown, but GC+ and HSV-2+ The probability is socially structured -
IDUs may be in sexual networks that contain non-injecting drug users and thus sexual transmission may extend to the community
HIV-positive by Gender/Sexuality (MSM=up triangle, WSW=down triangle, other female=circle, other male=square) by Hardest Drug Use Ever (from dark red to light pink: IDU, Crack, NI Heroin or Cocaine; blue=other)
SOCIAL network ties can carry influence: Within relationships To or from an individual Throughout a community or small group
Analyses of behaviors within relationships find: Risk and transmission behaviors are independently and significantly more likely in close relationships
Both drug users and their neighbors may be (or become) active in communicating health messages: survey findings about other-protective action in the prior 3 months by “hardest” drug used in last 3 months In the last 3 months, have you urged … 160 IDUs 61 crack smok ers 80 users of non- injected heroin or cocaine 90 marijuan a users 75 non- users of these drugs anyone to use condoms if they start a new relationship? not to use drugs? any drug injectors: 46% 51% 56% 64% 56% 54% 64% 48% 55% 41% to get into drug treatment? 54%64%40%28%25% to use needle exchanges? 38%13%15%2%4%
Research in many countries shows that safer norms are associated with safer behaviors such as consistent condom use and avoiding syringe sharing Urging others to behave more safely creates “external” social norms that flow through social networks
Prevention issues Network concepts let us develop ideas that focus on: 1. The individual client 2. The relationship 2. The client’s friends and partners 3. The risk community as a whole 4. The peer structure of communities that are trying to organize prevention and care This helps us get “outside of the box” of thinking only about the individual, but also keeps us from forgetting about her or him
Network Interventions Sessions in which IDUs bring in their peers can help reduce the index IDU’s risk behaviors (Latkin) Diffusion and indigenous leadership models of behavior and normative change have been shown to work by outreach projects and by Jeff Kelly and Wayne Wiebel Risk contact tracing Social contact tracing
Secondary syringe exchange Staff (often users or members of users’ friendship networks) give clients needles and other supplies to take to others and to retrieve if feasible Staff train clients in best ways to do this, including perhaps in referrals and recruitment; and learn from the secondary exchanger clients Secondary exchangers may train members of their distribution networks to be secondary exchangers too It can incorporate thousands of new IDUs into harm reduction activity. “Bundles” of supplies may be quite large. Evaluation by sequential cross-sectional design, with behavioral, normative and infection outcomes. Sampling perhaps by targeted sampling or respondent driven sampling Tom Valente has studied secondary exchange
Indigenous-Leadership-Focused Models Local leaders have their own interests at stake, and their own conceptions of risk and benefit. This may partially explain difficulties in replications of Kelly’s intervention in Glasgow and London gay venues.
Organizing communities for intervention and support Users’ groups exist and are engaged in fighting HIV and in providing advice to policy makers and programs in many countries So also do projects in which other community members and users work together In general, community organizing is built around members or participants recruiting their social networks to take part This has been shown both by empirical studies of social movements and by historical analyses of successful organizing efforts in a wide range of activities
Concluding thoughts (1) Networks can be used to recruit, to convey messages, to distribute supplies Their existence creates “contamination” problems for some individual-focused research designs A good program reduces HIV incidence and other harms. These harms are created by behaviors within networks, not just by disembodied behaviors. Reducing risk behavior (by the uninfected) and transmission behavior (by the infected) can have different implications depending where they are in community social networks and on the characteristics of their partners This implies that evaluating programs simply in terms of reducing risk behavior may be misleading.
Concluding thoughts (2): Program approach Street-based SEPs staffed in part by current IDUs and other network members Secondary syringe exchange and condom distribution Diffusion of information and persuasive arguments through networks Help users to organize to give advice and to take part in policy discussions Can greatly increase numbers, social network distribution, and geographic distribution of the intervention IF and ONLY IF the users’ culture and the general social and political environment allow it.