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Maximizing Impact and Return on Investments in STD/HIV Prevention Programs

Maximizing Impact and Return on Investments in STD/HIV Prevention Programs. David Wilson, Nicole Fraser, Marelize Gorgens and Zukhra Shaabdullaeva Global HIV/AIDS Program The World Bank 15 July, 2013 IUSTI Vienna. Maximizing impact and investment return. Why worry?

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Maximizing Impact and Return on Investments in STD/HIV Prevention Programs

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  1. Maximizing Impact and Return on Investments in STD/HIV Prevention Programs David Wilson, Nicole Fraser, MarelizeGorgens and ZukhraShaabdullaeva Global HIV/AIDS Program The World Bank 15 July, 2013 IUSTI Vienna

  2. Maximizing impact and investment return • Why worry? • Proven interventions? • Achieve with full implementation? • Actual implementation? • Investing smarter and implementing better?

  3. Why worry?Comparative disease burden of AIDS Death (%) 16% 5.6% 3.2% East Asia South Asia Sub-Saharan Africa Rao 2013 from http://www.healthmetricsandevaluation.org

  4. The end of AIDS? • Estimated national HIV incidence encouraging • Measured sub-national HIV incidence worrying

  5. Estimated national HIV incidence fell by 20% • 39 countries (23 African) - declines > 25% Estimated national incidence declines2001 - 2011 UNAIDS, 2012

  6. Measured sub-national HIV incidence(trial cohorts)

  7. Smarter investments, greater impact • Understand transmission dynamics • Use proven interventions • For the right people • In the right places

  8. The core transmission dynamics distinction: Concentrated, generalized and mixed epidemics Epidemics CONCENTRATED if effective SW (sex worker), MSM (men-having-sex-with-men) and IDU (injection drug user) programs would prevent wider epidemic Epidemics GENERALIZED if epidemics would persist despite effective SW, MSM and IDU programs Epidemics MIXED if transmission sustained BOTH by SW, MSM and IDU and wider population

  9. Concentrated, generalized and mixed epidemics Concentrated Generalized Mixed/uncertain

  10. Transmission dynamics:Indonesia’s contrasting epidemics in one country Jakarta’s concentrated epidemic Papua’s generalized epidemic Wilson, 2012

  11. Transmission dynamics: an improved Modes of Transmission model in Cross River State, Nigeria Old model < 20% concentrated transmission New model ~ 50% concentrated transmission

  12. Understanding transmission dynamics avoids misunderstanding – India example Mishra, 2012

  13. Concentrated epidemics:Why worry? UNAIDS, 2012

  14. Concentrated epidemics – SW • Why worry? • Proven interventions? • Achieve with full implementation? • Actual implementation? • Investing smarter and implementing better?

  15. Concentrated epidemics – SWWhy worry – SW HIV rates 13.5-fold higher 20% UNAIDS, 2012

  16. Concentrated epidemics – SWProven interventions • Concentrated SW epidemics - know what to do in real world at scale and have checked several SW epidemics • Effective SW programs have six integrated components: • Behavior change communication • Condom promotion • Tailored sexual health services • HIV testing and treatment • Solidarity and group empowerment • Supportive local and national legal environment

  17. Concentrated epidemics – SWProven interventions in Burkina Faso

  18. Concentrated epidemics – SWImplementation and coverage limited • 75% very low or don’t report • 91% of funding international • Services for MSW and TGSW almost non-existent 75% very low or no report UNAIDS, 2012

  19. Concentrated epidemics – SWLow investment in high impact SW interventions – Benin

  20. In India, targeted interventions alone may nearly eliminate HIV – at lower cost Blanchard, 2012

  21. The complexity of sex work in Africa poses a particular implementation challenge 2818 2-3

  22. Concentrated epidemics – MSM • Why worry? • Proven interventions? • Achieve with full implementation? • Actual implementation? • Investing smarter and implementing better?

  23. Concentrated epidemics – MSMWhy worry – MSM HIV rates 13.5-fold higher 20% UNAIDS, 2012

  24. Concentrated epidemics – MSMProven interventions? • Despite developed world successes , few developing country MSM programs have demonstrably reduced HIV incidence • PREP reduced HIV among MSM by 44% (90% among fully adherent) but we don’t even reach MSM in most developing countries with information and condoms • In developing countries, scarcely know how to reach hidden MSM, reduce stigma, deliver at scale and change policy • Still need to navigate between southern unwillingness to address male-male sexuality and northern temptation to frame response within western constructs

  25. Concentrated epidemics – MSMImplementation and coverage limited • 70% very low or don’t report • 90% of funding international - 19-21 LMIC reliant on external funding 70% very low or no report UNAIDS, 2012

  26. Concentrated epidemics – MSMFew reached by HIV prevention services

  27. Concentrated epidemics – IDU • Why worry? • Proven interventions? • Achieve with full implementation? • Actual implementation? • Investing smarter and implementing better?

  28. Concentrated epidemics – IDUWhy worry – IDU HIV rates 20-fold higher 60% UNAIDS, 2012

  29. Concentrated epidemics – IDUProven interventions? • Three proven interventions (plus other 6 WHO interventions) • NSP • OST • ART

  30. Concentrated epidemics – IDUProven interventions? NSP • HIV prevalence in 99 city study (MacDonald et al, 2003) 19% per year in cities with NSP 8% in cities without NSP OST • RCTs (Mattick et al, 2003) • Observational studies (Mattick, 1998) • Cochrane review (Gowing, 2008) • Amsterdam cohort – • 60% incidence reduction • Meta-analysis (Mcarthur BMJ2012) • 60% incidence reduction

  31. Concentrated epidemics – IDUImplementation and coverage limited 86% low coverage or no report UNAIDS, 2012

  32. Concentrated epidemics – IDULow access to basic services 92% 90% Million 85% IHRA, 2012

  33. Generalized epidemics • Why worry? • Proven interventions? • Achieve with full implementation? • Actual implementation? • Investing smarter and implementing better?

  34. Generalized epidemics: Why worry?Why they are so different? FHI, 2002

  35. Generalized epidemics: Why worry?Why they are so different? Sources of infection – KwaZulu-Natal (South Africa) example, 2012

  36. Generalized epidemics: Why worry?Why they are so different? National household HIV prevalence, Swaziland, 2012

  37. Generalized epidemicsDo we have proven approaches? Weiss, Abu_Raddad, Padian

  38. Generalized epidemics - VMMCDo we have proven approaches? • VMMC clinical trial efficacy at least 60% • VMMC longer term effectiveness greater 67% - 4.5 years, Kenya 73% - 4.8 years, Uganda 76% - 3 years, South Africa

  39. Generalized epidemics - VMMCWhat can we achieve with full implementation? 80% implementation will avert 3.4 million or 22% of new HIV infections in 14 priority countries Cost-effective - net savings per VMMC $1,100 at age 20 VMMC amortization 7 years at age 20 (11 years at 30 and 25 years at 45) Savings per circumcision Haaker, 2013

  40. Generalized epidemics - VMMCActual implementation is seriously off-target Total PEPFAR, 2013

  41. Generalized epidemics - TAsPDo we have proven approaches? • TAsP clinical trial efficacy 96%+ • TAsP real world effectiveness lower? • Infection 34% lower in area with 30%-40% ART coverage (the effect saturation point) than area with <10% coverage in KZN (Tanser et al, 2013) • Infection 26% lower in discordant couples in China - for transfusion or sexually infected but not IDU infected indexes (Jia, 2012) • No difference in discordant couples in Uganda (Birungi et al. 2013) • HIV infections continue to rise in highly treated MSM communities in developed countries (Wilson et al, 2012) • With ~85% on ART at CD350, Swaziland has measured HIV incidence of 2.4% on top of 26% adult prevalence (SHIMS, 2013)

  42. Generalized epidemics - TAsPDo we have proven approaches?

  43. Generalized epidemics - TAsPWhat does full implementation look like? 11 million17 million21 million26 million32 million • 9.7 million on ART - 26 million eligible at CD500 and 32 million eligible for “test and treat” “Test and treat” All HIV+ CD4 ≤ 200 CD4 ≤ 350 + TB/HIV HBV/HIV + CD4 ≤ 500 CD4 ≤ 350 + TB/HIV HBV/HIV 5 3 4 1 2 + TB/HIV HBV/HIV SD couples Pregnant Children < 5 Recommended until 2010 Recommended since 2010 • ART regardless of CD4 count for: • HIV-SD couples • Pregnant women Apollo et al, 2013

  44. Generalized epidemics - ARTWhat is actual implementation like? US treatment cascade - 28% virally suppressed

  45. Generalized epidemics - ARTWhat is actual implementation like? Retention on ART Retention below 60% after 5 years in Kenya and Malawi UNAIDS, 2012

  46. Generalized epidemics - ARTWhat is actual implementation like? Kranzer et al, 2013

  47. Generalized epidemics - ARTWhat is actual implementation like? Stadeli et al, 2013 Acquired HIV drug resistance in low resource settings

  48. Generalized epidemics - ARTWhat is actual implementation like? HIV drug resistance in ARV-naive populations SDRM = Surveillance Drug Resistance Mutations

  49. Generalized epidemics – Financial incentivesDo we have proven approaches? • Three World Bank RCTs show financial incentives reduce STI/HIV transmission • In Tanzania, people offered up to $60 each annually to stay STI-free had 25 percent lower STI prevalence (De Walque et al 2012) • In Malawi, girls and parents offered up to $15 monthly to stay in school had 60% lower HIV prevalence - whether they stayed in school or not(Ozler et al, 2012) • In Lesotho, adolescents offered a lottery ticket to win up to $50 or $100 every four months if they stayed STI and HIV-free had a 25% lower HIV incidence - 33% lower among girls and 31% in the $100 arm(De Walque et al 2012)

  50. Generalized epidemics – Financial incentivesDo we have proven approaches?

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