1. St Marys Hospital Ingrid V. Bassett, MD, MPH Massachusetts General Hospital Harvard Medical School May 25, 2010 Who Starts ART in Durban, South Africa? …Not Everyone Who Should

2. Conflict of Interest Disclosure Ingrid V. Bassett, MD, MPH Has no real or apparent conflicts of interest to report

3. Overview 2.9 million on ART in sub-Saharan Africa, but 6.7 million need it How much of this gap is due to failure to link to care after a new HIV diagnosis? What can be done to improve linkage? WHO, 2009

4. Road Map Retention versus Linkage Linkage in resource-limited settings Durban, South Africa study Strategies to improve Linkage

5. Poor retention well-documented Systematic review sub-Saharan Africa of adult patient retention in ART programs Non-research ART programs, 2000-2007 33 patient cohorts (>74,000 patients) Very high rates of loss ~40% not in care at 2 years: Loss to follow-up 56% Death 40% Rosen, PLos Medicine, 2007

6. Background: Poor retention substantial during scale-up Updated systematic review 2007-2009 >226,000 patients, 39 cohorts, 80% in Afr ~25% lost at 2 years, ~35% lost at 3 years Slightly better than before, but still substantial losses after ART initiation Routine M+E and PEPFAR reporting focus on ART patients Fox, Trop Med & Intl Health, 2010

7. Retention On ART

8. Linkage What is known about rates of linkage to HIV care after a new HIV diagnosis? What are risk factors for failing to enter care? Do these differ by setting? HIV TestCD4 count Training 1,2,3 On ART Psychosocial Assessment

9. Determinants of mortality and non- death losses: Cape Town Community-based ART program, 2002-2005 1235 enrolled in ART program 121 died (46% pre-tx; 40% early tx) Risk: symptomatic disease and CD4 <100 After first year of ART, low mortality rate <1%/year High risk of pre-ART and early ART deaths Lawn, AIDS, 2006

10. What is rate of mortality and retention pre-ART in Uganda? TASO ART Clinic, Jinja, rural Uganda Focus on 4-8 week pre-ART screening period 26% of ART-eligibles did not finish screening Risk: lower median CD4, male gender Increased over time with clinic expansion Home visits to ascertain status 30% on ART with different provider 25% alive and not on ART (44% due to transport) 28% died 17% LTFU High rate of pre-ART mortality Amuron, BMC Public Health, 2009

11. Why failing to link in Malawi? Cross-sectional study Rural Malawi (MSF), 2004-2007 Defaulters missed appointment by >1 mo 874 adults pre-ART traced, 71% found: 51% dead, most within 3 months of last visit Reasons for defaulting: stigma, dissatisfaction with care/staff, perceived improved health, transport costs McGuire, Trop Med & Intl Health, 2010

12. From HIV test through ART start in Mozambique: a retrospective study Routine care data from 2 HIV care networks HIV tested 2004-2005, first year after free ART in public sector 7005 with HIV Only 56% enrolled ART clinic within 30d 1506 ART-eligible Only 31% start ART within 90d of CD4 Micek, JAIDS, 2009

13. Failure to Link: Open questions What proportion of newly identified HIV- infected dont start ART? What are the risk factors for failing to link to care? Few prospective data about losses and mortality before HIV clinic entry Valuable to design interventions to improve linkage to HIV care

14. Who Starts ART in Durban, South Africa? …Not Everyone Who Should Ingrid V. Bassett, MD, MPH Susan Regan, PhD Senica Chetty, MSc Janet Giddy, MBChB, MFamMed Lauren M. Uhler, BA Helga Holst, MD, MBA Douglas Ross, MBChB, MBA Rochelle P. Walensky, MD, MPH Kenneth A. Freedberg, MD, MSc Elena Losina, PhD St Marys Hospital

15. Background: HIV in South Africa > 5 million people HIV-infected Largest ART program in the world Only ~40% of HIV-infected who need ART are receiving it Few data why HIV-infected fail to link to care WHO 2009; PEPFAR 2008; Lawn, AIDS, 2008

16. Objectives To evaluate rates of ART initiation within 12 months of a positive HIV test in Durban, South Africa To identify baseline factors that predict failure to be on ART at 1 year

17. Methods: Two Study Sites Prospective, observational cohort Sites: Outpatient departments in Durban McCord (urban) St. Marys Mariannhill (semi-rural) Partially government subsidized Patients pay a fee for care PEPFAR-funded HIV clinics

18. Methods: Study population Adults (18y) English or Zulu speaking Enrolled prior to rapid HIV test Enrolled November 2006-October 2008 Follow-up through June 2009

19. Methods: Data collection Baseline enrollment interview 6, 12 month questionnaire Domains: demographic, geographic, clinical Electronic medical record review at enrollment site: CD4, ART start

20. Methods: Two Outcomes 1) Obtaining CD4 count within 90 days 2) ART initiation within 12 months for eligible patients CD4 200 /µl within 90 days of HIV test ART initiation at study site documented in medical record

21. Methods: Data analysis Predictors of failing to initiate ART evaluated with multivariate logistic regression Kaplan-Meier curve of time to ART initiation Mortality pre- and post-ART initiation

22. Enrolled 2,775 HIV-negative 1,308 HIV-infected 1,467 HIV Test No test/result: 71 Indeterminate: 6 54% HIV prevalence Screened 3,401 Results: Cohort enrollment Bassett, AIDS, 2010

23. HIV-infected cohort characteristics Female 54% Median age 34 yrs (IQR 28-41) Median follow-up time12 mos (IQR 8-14) Follow up available 70% Bassett, AIDS, 2010

24. HIV-infected 1,467 CD4 count within 90 days Yes 607 No 862 CD4<200/μl 368 CD4200/μl 237 59% no CD4 within 90 days Results: CD4 count within 90 days 61% CD4<200/µl ART eligible at baseline Unknown 2 Bassett, AIDS, 2010

25. HIV Tested* HIV+ CD4/results Eligible for ART Start ART *Screened 11/06-10/08, enrolled in study and have known HIV status 368 How many start ART? Failure to obtain CD4 Failure to start ART when eligible Bassett, AIDS, 2010 154 605 2,775 1,467

26. Results: Long delay from HIV diagnosis to ART start P<0.001 Males: 40% started ART by 6 months Females: 55% started ART by 6 months Bassett, AIDS, 2010 days P<0.001

27. Results: Predictors of failure to start ART within 12 months Male gender RR 1.5 (1.1-2.1) No HIV+ family/friendRR 5.1 (1.8-14.9) Adjusting for: age, CD4 count, prior HIV test, work outside the home Bassett, AIDS, 2010

28. Results: High rate of mortality 15% of HIV-infected cohort (216 deaths/1,467) 21% of ART eligible cohort (76 deaths/368) % dead HIV+ cohort with CD4 P<0.001 CD4 (/µl) strata Bassett, AIDS, 2010

29. High rate of mortality pre-ART Most patients died pre-ART or with unknown ART status P<0.001 CD4 (/µl) strata Overall Pre-ART % dead HIV+ cohort with CD4 Bassett, AIDS, 2010

30. Limitations Sites may not be representative of public sector hospitals in South Africa 30% of pre-ART patients were unreachable Likely underestimates mortality and ART initiation that occurred at non-study sites Bassett, AIDS, 2010

31. Study conclusions Substantial pre-ART loss along care path Men less likely to initiate ART Severe immune suppression at diagnosis Long delays to ART initiation High rates of pre-ART mortality Bassett, AIDS, 2010

32. Implications Promote early HIV diagnosis and care Monitor mortality and losses pre-ART Improve access for men Interventions needed to improve linkage to care/minimize delays Following new HIV diagnosis After ART eligibility determined

33. Learning from on-ART strategies: patient tracking 2 ART facilities Lilongwe, Malawi, 2006-09 Patients who missed clinic appt >3 weeks 2,653 patients identified, 85% traced by phone and home visit 30% died 1,158 found alive, not transferred 74% returned to clinic (women, age >39 at ART start) Tweya, Trop Med & Int Hlth, 2010

34. Learning from on-ART strategies Patient tracers phone calls or home visits to ascertain vital status, help subjects return to care Proactive adherence support, including home visits, community-based collaborations Transportation vouchers Eliminate co-pays Reliable (electronic) monitoring Geng, JAMA, 2008; Ochieng, IAS, 2007; Tweya, Trop Med & Intl Health, 2010; Rosen, Trop Med & Intl Health, 2010; Etienne, Trop Med & Intl Health, 2010; Forster, Bull WHO,2008

35. Learning from on-ART strategies: efficiency Johannesburg 4-month pilot study of telephone tracing by social worker Average $432/patient returned to care Lessons learned from this and others: Maintain updated contact information Capacity to know about clinic transfers Capacity to access national death registry Rosen, Trop Med & Intl Health, 2010 Bassett, JAIDS, 2009; Mwanaga, CROI, 2008;Tweya, Trop Med & Intl Health, 2010;

36. Learning from US linkage to care trial HIV-infected, recently diagnosed, multi-site US RCT case management vs standard of care Primary outcome in-care at 12 months A higher proportion in intervention arm visited HIV clinician at least once within 6 months (78% versus 60%, p < 0.01) and at least twice within 12 months (64% versus 49%, p < 0.01) No similar RCT has yet been performed in resource-limited settings Gardner, AIDS, 2005

37. Upcoming NIMH-funded linkage to care trial Multi-site RCT in Durban starting in 2010 Assess clinical impact and cost- effectiveness of a health system navigator assigned in the outpatient setting Navigator in-person, SMS, phone contacts Evaluate linkage to HIV care and TB treatment completion

38. Acknowledgements Durban Team Janet Giddy Senica Chetty Douglas Ross Lindeni Sangweni Aletta Maphasa Success Mncwabe Yolisa Mgobhozi Bongiwe Mdadane Matilda Mazibuko Helga Holst Study participants at McCord and St. Marys Hospitals, Durban US Team and Funders Rochelle Walensky Ken Freedberg Elena Losina Susan Regan Sarah Bancroft Harv Univ Program on AIDS Harvard CFAR AI60354 NIAID K23 AI068458 Harvard Catalyst Grant Upcoming trial: NIMH R01 MH090326

39. St Marys Hospital