ADOLESCENTS AND HIV: WHAT IS NEW IN PREVENTION IAS Rome July 2011 Audrey Pettifor, PhD MPH Department of Epidemiology, University of North Carolina.

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Presentation transcript:

ADOLESCENTS AND HIV: WHAT IS NEW IN PREVENTION IAS Rome July 2011 Audrey Pettifor, PhD MPH Department of Epidemiology, University of North Carolina

Overview  Epidemiology of HIV infection among adolescents and young adults globally  Unique characteristics of adolescence  Determinants of infection among adolescents  Review of the evidence on prevention interventions to date

Young people are at high risk New Infections = 2.6 million Under 15 14% Aged % Aged % NOTE: Calculations are estimates. SOURCE: Kaiser Family Foundation calculations based on UNAIDS, Core Slides: Report on Global AIDS Epidemic, Young People as Percent of Global Number of New HIV Infections, 2009

In sub-Saharan Africa, girls make up nearly 70% of all young people living with HIV ♀ ♀ ♀ ♀ ♀ ♀ ♂ ♂ ♂ ♂ ♂ ♂ Sub-Saharan Africa (4.0 Million) Latin America & the Caribbean (300,000) South Asia (210,000) East Asia & Pacific (210,000) Middle East & North Africa (89,000) CEE/CIS (70,000) Source: UNAIDS, 2009 AIDS Epidemic Update ♀ Female ♂ Male The size of the pie charts indicates the number of young people infected

HIV prevalence by age and gender among South Africans age Males Females 95% Confidence Interval SOURCE: Pettifor A, et al. AIDS 2005, 19:

Good news  HIV prevalence among young people aged years declined significantly between 2000 and 2008 in 10 of 21 high burden 1  Evidence from the majority of these countries that young people are changing behavior towards ‘less risky’ behaviors– however, some trends only observed for some behaviors, in rural or urban areas or among only one gender. 1 SOURCE: countries(The International Group on Analysis of Trends in HIV Prevalence and Behaviours in Young People in Countries most Affected by HIV. STI 2010

Why are adolescents at risk?  Adolescence is a time of important biological and developmental change as well as change to family and social contexts, which may increase HIV risk  Biological and developmental factors (bio- behavioral and neurobiological processes) 1 :  Heightened risk-taking behaviors  Difficulties controlling behavior and emotions  Pressure to assert individuality and to ‘fit in’ 1 SOURCE: Comm. On the Science of Adolescence. The science of adolescent risk-taking: IOM Workshop report

Adolescence is a time of transition  Changes in context that may increase risk:  Leaving school  Leaving home  Entering first serious relationship (increase in sexual contact/frequency/partners)  First pregnancy  Context of adolescent sex that may affect risk:  Episodic sex that is less likely to be protected  Limited access to prevention and knowledge– lack experience/self-confidence/skills  Many youth have not yet had sex (opportunity to intervene) and affect future trajectory of behavior

Importance of Context: Peers/Partners, Family & Community

Determinants of infectiousness and susceptibility in young women  Over 300 determinants identified associated with sexual behavior in youth (IOM report 2010)  Determinants at various levels  Biologic  Behavioral  Community/Contextual  Structural  Contextual and Structural factors have been overlooked to date

Limitations of interventions to date  Evidence that HIV prevention can change knowledge, attitudes, and behavior- most interventions are individually focused  Few interventions are rigorously evaluated  Few studies with biological endpoints  Interventions addressing structural factors are limited  Few address multiple risk factors –combination prevention

Interventions  School based  Peer-led  Mass Media  New Technology  Bio-Medical  Structural: Cash transfers

School based interventions  School based sexual health interventions-  No evidence that they increase risk, however, evidence is limited with regard to reducing risk behavior (Paul- Ebhohimhen et al. BMC Public Health 2010; Michielsen K et al. AIDS 2010)  Kirby review of school based sex and HIV education programs finds that 2/3 of programs globally have had a significant positive impact on behavior, although impacts are modest (Kirby D et al. J Adoles Health 2007 Stronger evaluation needed– few have biologic outcomes

Peer-led interventions  Peer education is popular—59% of programs in SSA  Evidence suggests that peer-led programs can have positive impacts on knowledge and condom use (Maticka-Tyndale E et al. Eval and Program Planning 2010; Medley A et al. AIDS Ed and Prev 2009)  Evaluations to date have been weak  Effects are modest  Need for best practices and process evaluation to understand what makes programs successful (Maticka- Tyndale highlights some attributes)

Mass Media  Media Interventions  Mass media have consistent, measurable and positive impacts on condom use (Snyder et al APHA in review; Bertrand J Health Ed Rev)  Can increase knowledge, risk perception, encourage behaviors or link to care (e.g. uptake of VCT)  Reach large audiences and thus cost- effective for the change incurred

New technology  Cell phone based interventions  Ralph DiClemente- HORIZONS cell phone intervention, significant declines in risk behavior and CT- IAS Vienna 2010  Mymsta/loveLife, South Africa– cell phone based social networking site– access to health information, games, counselors  Computer/Internet based interventions/Social Networks  Facebook, MySpace  Just/Us– RCT of 1588 youth in US intervention on facebook. Games, video, blogging, threaded discussions and quizzes, all about sexual health ( PI Sheana Bull)  Web based  Healthmpowerment.org– young, Black MSM in the US. Included live chats, quizzes, personalized health and “hook-up/sex” journals, and decision support tools for assessing risk behaviors (PI Hightow- Weidman L, AIDS Ed and Prev 2011)

Biomedical interventions  MTN 021– phase II study.1% tenofovir gel– 90 adolescents girls years randomized in 2:1 ratio– safety study in US (ATN and MTN, PI Craig Wilson)  FACTS 002– phase II study. 1% tenofovir gel– to be conducted in South Africa among yr olds (Ps Helen Rees and Linda-Gail Bekker)  Vaccine preparedness– SASHA and HVTN studies to assess acceptability, retention and incidence (PI Linda-Gail Bekker)  Prep  Male circumcision  HIV testing and linkages to care (test and treat)

Structural Interventions: Cash Transfers  8 studies using cash transfer/incentives/reducing structural barriers to schooling to reduce HIV risk  5 completed and 3 underway  5 provided a cash transfer, 1 provided savings account matching (SM), and 2 provided assistance with school costs (SC), such as school uniforms, fees, or supplies  The focus included school attendance (SA), school completion (SC), and completion of health promotion activities (HP), such as STI/HIV testing, learning one’s HIV status, HIV treatment seeking, and participation in wellness activities  Results seem promising in terms of reducing risky behavior but only 1 study to date has a biologic endpoint

Evidence of Cash Preventing HIV  SIHR trial in Malawi—RCT, 3 arms: unconditional cash, conditioned cash on school attendance, control  Eighteen months after the program began, the HIV prevalence among program beneficiaries was 60% lower than the control group (1.2% vs. 3.0%)  Change in the risk profile of sex partners seems key. Intervention girls less likely to have older partners and to have received cash from the partner ( The World Bank. A cash transfer program reduces HIV infections among adolescent girls. The World Bank Development Research Group. [Accessed online June 19, 2011: at  HPTN 068 and CAPRISA 007 RCTs both underway in South Africa with HIV incidence endpoints

The Future: Combination Prevention

Conclusions  Young people are disproportionately at risk of HIV infection in both the US and globally—young women are at particularly high risk in SSA  Structural and contextual factors are important in determining risk, more so than traditional individual level behaviors  There are innovative interventions being tested that address structural drivers of risk and harness new technologies  Ultimately, combination prevention is essential

Acknowledgments  Nadia Nguyen, UNC  Molly Rosenberg, UNC  Ralph DiClemente, Emory  Sheana Bull, UC Denver  Judy Cornelius, UNC Charlotte  Susannah Allison, NIMH  Catherine MacPhail, WRHI  Linda-Gail Bekker, DTHF