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HIV/STD Risk Behaviors in Methamphetamine User Networks

HIV/STD Risk Behaviors in Methamphetamine User Networks. Steve Shoptaw, Ph.D. Pamina Gorbach, Dr.P.H. UCLA. Objectives. Examine diffusion of HIV and STDs through sexual networks of drug using and non-drug using, high-risk individuals in Los Angeles County at the: Individual-level

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HIV/STD Risk Behaviors in Methamphetamine User Networks

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  1. HIV/STD Risk Behaviors in Methamphetamine User Networks Steve Shoptaw, Ph.D. Pamina Gorbach, Dr.P.H. UCLA

  2. Objectives Examine diffusion of HIV and STDs through sexual networks of drug using and non-drug using, high-risk individuals in Los Angeles County at the: • Individual-level • Partner-level Among: • Men who have sex with men (MSM) • Men who have sex with men and women (MSM/W) AND Their partners….

  3. Overview • Stimulant use, particularly methamphetamine use, effects the transmission of HIV and STDs in Los Angeles County and the urban Western U.S. • Methamphetamine is a “sex drug” that facilitates commission of HIV-related sexual risk behaviors in MSM and MSM/W • Injection risks are a relatively minor component of the spread of HIV in the West

  4. The Los Angeles AIDS Epidemic:Cumulative Male AIDS Cases Los Angeles*United States** MSM 76% 57% MSM and IDU 7% 8% IDU 6% 24% Other 11% 11%

  5. Methamphetamine and HIV in MSM: A time-to-response association?

  6. I was so tweaked….. …I didn’t care how he screwed me.

  7. Why Methamphetamine for MSM? • Methamphetamine use and increase in sexual libido among MSM and MSM/W first noted in 1970s • Increased energy • Decreased appetite • Euphoria • Psychomotor agitation • Heightened interest in sex • Delayed orgasm – longer and rougher sex episodes • Potential for this group to be “bridge” for infectious disease to general population

  8. Drug Use and Infection Risks for MSM and MSM/W • Incidence of HIV infection among San Francisco MSM is 1.2-2% per 100 ppy (Stall et al., 2000) • Incidence in Seattle STD clinic is 26% per 100 ppy (Golden, 2003) • Local and national increases in infectious diseases and risk behaviors among MSM and MSM/W •  gonorrhea •  risk behaviors among HIV- and HIV+ (Craib et al., 2000) and among MSM on HAART (Vanable et al., 2003) • Caucasians prefer methamphetamine; men of color prefer alcohol; cocaine

  9. Factors Effecting STI/HIV Transmission among Drug Users for Any Sexual Event • The risk behaviors (± IDU, vaginal/anal sex, with/without barriers, insertive/receptive, using drug/not) • The partnership (1° partner/not, monogamous/concurrent, gender and sexual network characteristics) • The social context (high risk environment/not)

  10. Types of partnerships Partnership dynamics Concurrency Condom use Drug use Disease transmission How do Partnership Dynamics Influence HIV/STD Transmission? ?

  11. Study Approach • Collect biomarkers and self-report data from index participants and their sexual partners to model the diffusion of STIs/HIV among drug users • Analysis proposes triangulation of biomarkers (blood, urine for HIV, gonorrhea, syphilis, methamphetamine, cocaine, opiates, marijuana) to provide prevalence, incidence on STI/HIV • Qualitative information describes partnerships • Modeling to evaluate movement of infections and drug use

  12. Representative Sampling Cohort Design (N=1,200) Index Participants and Nominated Participants Drug-using MSM/W and Sexual Partners (n=240) (96 males, 96 females) Drug-using MSM and Sexual Partners (n=240) (96 males) Non-drug-using MSM/W and Sexual Partners (n=240) (96 males, 96 females) Baseline STD/Drug Self-Report 12 Months STD/Drug Self-Report 6 Months Drug Self-Report

  13. Design Discussion • Observing infectious disease, sex risks, and partnership factors among MSM and MSM/W drug users over time in representative cohorts allows accuracy in predicting spread of HIV/AIDS in Los Angeles region • Non-drug using MSM/W comparison group • One-year observation period for completion of the study within time and budget • Small, ego-centered networks have limits, but can be completed • Ethnography may provide description on larger networks

  14. Network Structure and HIV/STDs • Individual and partnership-level data can provide sufficient data to model spread of STDs in a full network (Eames et al., 2002) • Integration of ethnographic, self-report, and biological markers using modeling • CASI to measure amount of behaviors • Ethnography to capture meaning of behaviors • Biomarkers to detect drug use, STD/HIV status

  15. Enrollment of MSM, MSM/W • Relatively public places frequented by the men (strolling areas) or high-risk venues (bathhouses, sex clubs, parks, bookstores) • STD clinics • Representative sampling plan • 18-20 men enrolled weekly plus their sexual partners

  16. Eligibility Criteria: Index Participants • Behaviorally identified MSM, MSM/W • Drug users must self-report monthly use over past 6 months and on 2+ occasions in past 30 days • Alcohol users must report 5+ drinks per drinking day at least monthly and on 2+ occasions in past 30 days • Willing to provide at least 1 or 2 (for MSM/W, 1 male, 1 female) sexual partners with information about contacting study staff to consider enrolling

  17. Partner Participants • Maximum of 480 participants; 120 female • Must be male or female sexual partner of an index participant • No known methods for implementing a probability-based sampling frame for partners • May select for stable partners, though >25% of partnerships among youth seen in STD and FP clinics dissolve in 3 months; 60% in 1 year; 8-9 weeks average duration (Gorbach, 2003)

  18. Two Sites (1) Hollywood, West Hollywood, Silverlake areas of Los Angeles • Highest concentrations of MSM and MSM/W of color in Los Angeles County (2) Long Beach, Belmont Shore areas Venue based sampling to occur at L.A. County and Long Beach STD clinics

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