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Schneider, Cornwell, Ostrow, Michaels, Nelson, Lindsay, Friedman, Schumm, Laumann

Network mixing and network influences most linked to HIV infection and risk behavior in a Black MSM (BMSM) HIV epidemic . Schneider, Cornwell, Ostrow, Michaels, Nelson, Lindsay, Friedman, Schumm, Laumann. NCRR U54 RR023560 and NIDA R03 DA026089.

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Schneider, Cornwell, Ostrow, Michaels, Nelson, Lindsay, Friedman, Schumm, Laumann

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  1. Network mixing and network influences most linked to HIV infection and risk behavior in a Black MSM (BMSM) HIV epidemic Schneider, Cornwell, Ostrow, Michaels, Nelson, Lindsay, Friedman, Schumm, Laumann NCRR U54 RR023560 and NIDA R03 DA026089

  2. Black MSM in the US are disproportionately at risk for HIV (CDC 2009) • Sexual network analysis explains high STI rates within different racial groups (Laumann 1999) • Disassortative mixing - between a high-risk core and low-risk periphery- among blacks is linked to high STI rates compared to whites • Less work has focused on social network mixing • Social networks facilitate the diffusion of information and innovation (Valente 2010) • Specific features of social networks could both explain current disparities and illuminate points for network-based intervention to prevent HIV

  3. Mixing within social* and sexual† networks by risk behavior and HIV status

  4. Conclusion • Highly assortative mixing was evident in the sex network while contact between high and low risk individuals was most apparent within socialnetworks. • Disassortativemixing in the sex network was most evident with respect to UAI among HIV infected respondents • Additional prevention efforts (prevention for positives) for younger B-MSM with HIV are warranted • For UAI having at least one network member who was not disapproving of a behavior (an enabler) in the social network was influential on the respondent’s behavior; a finding not observed in the sex network. • These findings suggest that future HIV prevention interventions may be made more potent by incorporating and potentially altering social network mixing patterns, including behavioral norms within the networks, as well as the relationships with specific individuals within the network

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