Effects of an HIV/AIDS peer prevention intervention on sexual and injecting risk behaviors among injecting drug users (IDUs) and their risk partners in.

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Effects of an HIV/AIDS peer prevention intervention on sexual and injecting risk behaviors among injecting drug users (IDUs) and their risk partners in Thai Nguyen, Vietnam: a randomized controlled trial V.Go, C. Frangakis, N. Le Minh, T. Viet Ha, T. Thi Mo, C. Latkin, T. Sripaipan, W. Davis, P. The Vu, V. Minh Quan 1 Johns Hopkins Bloomberg School of Public Health 2 Thai Nguyen Center for Preventive Medicine

Background Globally, 30% of new HIV infections occur in injecting drug users (IDUs). 1 HIV-related sexual and injecting risks persist among IDUs. Peer and network interventions have been shown to be effective at reducing HIV risks among IDUs in different settings. 2 1 Wodak, Latkin, 2003; Des Jarlais, 1995; Garfein, 2007; Sherman, 2009; Hammett, 2006

HIV epidemic is concentrated among IDUs in Vietnam Reported # of IDUs: 274, % of HIV infections are among IDUs 1 Prevalence of HIV 2  General population: 0.04%  IDUs: 18% Marginalized population ________________________ 1 The Socialist Republic of Viet Nam, Ministry of Health of Vietnam, 2008

Thai Nguyen, Vietnam Thai Nguyen

Trial objective To assess the efficacy of a behavioral, peer network HIV prevention intervention among IDUs in Vietnam on reducing HIV sexual and injecting risk behaviors. Primary outcomes: – sharing injecting equipment – unprotected sex

Study overview Two arm randomized controlled trial Intervention: prevention messaging delivered via existing risk networks Index members: HIV-negative IDU males living in Thai Nguyen Province Network members: injected drugs and/or had sexual intercourse w/ index in past 3 mos.

Screened at Baseline N=1434 Intervention N=465 Participants with a Complete Network Group* N=924 Control N=459 *Complete Network Group = 1 Index Member + At least 1 Network Member

Recruitment, randomization & data collection Participants recruited by field workers who were current or former IDUs Block randomization Face-to-face interviews at study site & HIV testing and counseling (HTC) per WHO guidelines at baseline, 3, 6, 9 and 12 months

Intervention Index  Content: Harm reduction, communication strategies, and problem solving  Delivery: 2 facilitators leading didactic, interactive discussions and role-playing  Timing: Two-hour sessions weekly for six weeks; booster sessions at 3, 6, and 9 months Network received intervention content via their index.

Results 1.Total of 935 participants (index = 419; network = 516) 2.Overall retention rate: 85% 3.Among those who dropped out, main reasons included incarceration and moving out of province. 4.75% of index participants attended at least 4 out of 6 sessions.

Baseline characteristics of sample (n = 935) ControlIntervention Age Education Primary10.1%10.4% Secondary42.1%40.9% High School47.8%48.7% Married32.2%33.5% Full-time employed58.8%58.0% Shared needle 3 mos24.2%27.3% Unprotected sex 62.2%60.9%

Wald Test for Follow-up Visits: W=5.95, p=0.20

Wald Test for Follow-up Visits: W=12.2, p=0.02

Secondary analyses Secular trends Social desirability bias Contamination Telescoping Missing HTC sessions

Exploration of pattern of missed HTC visits and % with unprotected sex. Among participants who attended baseline and all 4 follow-up assessment visits, no difference between trial arms. Among those who missed interim visits, the control was more likely to report unprotected sex than the intervention (p<0.01).

Summary of intervention effect Both arms decreased injecting and sexual risk behaviors after baseline. At the 12 month visit, the intervention arm was significantly less likely to have unprotected sex as compared to the control arm. By accounting for missed visits, we found that the intervention had a lasting effect on sexual behaviors compared to standard HTC.

Implications Programmatic  Peer network interventions may be effective in facilitating longer term sexual risk behavior change.  HTC may be sufficient for changing injecting risk behaviors. Future Research  Explore the impact of participating in trial procedures.  Sustainability of effects.

Acknowledgements  Thai Nguyen Center for Preventive Medicine Funding  Fogarty International AIDS Research Program  NIMH# 1 R01 MH

Summary of secondary analysis No evidence of selection bias, social desirability, telescoping, secular trends or contamination. HTC may have reduced injecting behaviors. HTC may have had a short term impact on sexual behaviors, but the intervention had a longer term impact.

In Vietnam, as in many countries, the HIV epidemic is concentrated among IDUs 1 Estimated # of IDUs: 274, % of HIV infections are among IDUs 2 Prevalence of HIV 1  General population: 0.04%  Sex workers: 3%  MSM: 17%  IDUs: 18% ________________________ 1 The Socialist Republic of Viet Nam (2010). The fourth country report on following up the implementation to the declaration of commitment on HIV and AIDS. 2 Ministry of Health of Vietnam (2008). The third country report on following up the implementation to the declaration of commitment on HIV and AIDS (reporting period: January 2006-December 2007).

Secondary Analyses Secular trends- no difference by times of enrollment Social desirability bias- sero-conversions explained by self-reported risk behaviors Contamination- HIV discussions did not increase in control arm Telescoping- Among those who missed a visit, no difference in outcomes prior and after the missed visit. Missing HTC sessions

Analyses Intention to treat analysis Missingness of measures at different visits addressed through multiple imputation Secondary analyses conducted to explain findings of primary analyses

Effect (I-C) of intervention on needle sharing Indexes (n = 417) Effect (I-C), % (se) Wald Test (2-5) 0(2) -1(1) 6 (3) 3(2) 3(2) W = 3.74, p = 0.44 Networks (n = 2*417) Effect (I-C), % (se) Wald Test (2-5) 5(3) 0(1) 0(1) 4(2) 1(1) W = 5.95, p = 0.20 *Multiple imputations

Effect (I-C) of intervention on unprotected sex Indexes (n = 417) Effect (I-C), % (se) Wald Test (2-5) 4(5) 1(5) 5(6) 9(6) -10(5) W = 10.8, p =.03 Networks (n = 2*417) Effect (I-C), % (se) Wald Test (2-5) 2(4) -1(4) 2(4) 3(4) -10(4) W = 12.2, p = 0.02 *Multiple imputations