State of the science nieves rivera

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State of the science nieves rivera

  1. 1. The San Francisco Perspective: Combination Prevention Technologies Israel Nieves-Rivera Director, Community Engagement and Policy Unit HIV Prevention Section Manager, Office of the Director of Population Health and Prevention San Francisco Department of Public Health SYNChronicity Meeting Arlington, VA April 20, 2012
  2. 2. IN 2006 THE HEADLINES SAID: “Pluto Not a Planet, Astronomers Rule”
  3. 3. REACTIONS TO THE INFORMATION! 3
  4. 4. CITY AND COUNTY OF SAN FRANCISCO DEPARTMENT OF PUBLIC HEALTH (PARTIAL ORGANIZATIONAL CHART) Director of Health PCSI Co-Champion Jail Health SF General Hospital Community Health Population Health & Programs Prevention-Health Officer PCSI Co-ChampionForensic AIDS Hospital Based Health Maternal, Child & Project Centers Adolescent Health Community Health STD Prevention & Control HIV Health Services Promotion & Prevention UCSF Partnership (Ryan White Programs) PHP Clinic (ward 86) Tuberculosis Control Public Health Preparedness Community Health Care & Response UCSF Partnership Parnasus Community Oriented Communicable Disease Primary Care (COPC) Control & Prevention Environmental Health & Includes 15 clinics where OSH primary care is provided HIV Prevention SF Community Clinic by the health Consortium department Public Health Laboratory HIV Epidemiology Emergency Medical Services HIV Research 4
  5. 5. Population Health And Prevention SF Health Department and Affiliated Clinics SFDPH manages and implements a robust portfolio of HIV research and works in 5 collaboration with academic, clinical and community partners
  6. 6. SF HAS ALWAYS STRIVED TO CREATE A COMPREHENSIVE RESPONSE TO HIV•HIV testing •Linkage to medical care•Partner services •Behavioral Health Services•STD prevention and treatment •Home Health Service•Addressing drivers and co-factors of HIV •Non-medical case management•Linkage to medical •Food Bank / Home-delivered meals•Risk reduction activities •Client Advocacy-related services•Community mobilization efforts HIV and STD HIV Care and •Emergency financial assistance•Public information efforts Prevention Support •Legal services•Condom distribution •Housing services•Syringe access Services •Oral health care•PEP •Outreach services Surveillance, Primary Care Evaluation•Core Surveillance and HIV •Engagement in care•Incidence Surveillance and •Treatment Adherence treatment•Medical Monitoring Research •Medical Case management•NHBS •ADAP•Vaccine studies •Community Health Care•PrEP research •HIV specialty medical care•HIV drug resistance testing •Treatment Guidelines •STD and TB 6 Source: Nieves-Rivera, 2010
  7. 7. SAN FRANCISCO’S APPROACH TO MAXIMIZING THE CONTINUUM OF PREVENTION, CARE AND TREATMENT Primary HIV SurveillancePrevention Efforts Testing Diagnosis Primary Care Treatment Virologic HIV Suppression• PrEP, PEP, condoms, syringes Linkage Engagement Engagement• Drivers / Retention / Retention1. Substance use2. Alcohol3. Meth4. Crack Routine Mental Health Treatment Adherence Medical Services5. Poppers6. STDs, # of Testing Substance Use Medical Case partners Treatment Management  Linkage Community & Partner Housing ART Guidelines Testing Services Support Uptake STD & PCSI LINCS: Linkage, Navigation Engagement & Partner Services & Retention Team 7
  8. 8. UNDERSTAND THE HIV EPIDEMIOLOGY IN YOUR JURISDICTION• Identify • Identify the • Identify the viral populations at underlying burden in your greatest risk for conditions that are jurisdictions new infection + directly linked to a + • Identify• Populations with large number of populations living greatest new HIV infections with HIV /AIDS disparities in your (PLWHA) with• Percentage of jurisdictions greatest HIV health PLWHA that are disparities unaware of their HIV status Identify priority interventions to optimize health outcomes for PLWHA and avert new HIV infections 8
  9. 9. GREATEST RISK FOR ACQUISITION OF HIV AND UNAWARE OF HIV STATUSGreatest risk for new infections: • There are an estimated 723 new HIV infections per year in SF • An estimated 96% of new HIV infections are among males who have sex with males (MSM), injection drug users (IDU), and transfemales who have sex with males (TFSM) • There are very few cases of non-IDU heterosexual HIVGreatest Disparities: • White MSM • African American MSM • Latino MSM • TFSMUnaware of HIV status: • It is estimated that 17% (15%-20%) of San Franciscans are unaware of their HIV status Source: SF HIV Surveillance and HIV Prevention Plan
  10. 10. HIV IS ENDEMIC IN SF4500 Gay men/MSM: Endemic40003500 Injection drug users: Endemic30002500 Heterosexuals: Neither2000 epidemic nor endemic15001000 500 0 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2007 2008 10 Source: McFarland, 2009
  11. 11. DRIVERS OF HIV IN SFDriver: An underlying condition that is directly linked to a largenumber of new HIV infections in San FranciscoPrevalence of 10% or greater: • A driver has at least 10% prevalence among one of the high- risk populations where the bulk of new infections occur (MSM, IDU, TFSM)Two-fold increase in risk: • A driver is an independent factor for HIV making a person in a high-risk population at least twice as likely to contract HIV as compared to someone who is not affected by the driver.Drivers of HIV in SF: • Cocaine and crack use • Popper use • Heavy alcohol use • Gonorrhea • Methamphetamine use • Multiple partners Source: SF HIV Prevention Plan
  12. 12. IDENTIFY THE VIRAL BURDEN IN POPULATIONS 12 Source: Das, et al. 2010
  13. 13. IDENTIFY SUB-POPULATIONS WITH HIGH VIRAL BURDEN Overall N (%) Mean CVL*San Francisco 12,512 (100) 23,348 Sub-Populations N (%) Mean CVL*Transgender 291 (2) 64,160Not on treatment 2924 (23) 40,056Not engaged in care 4637 (37) 36,992MSM-IDU 1791 (14) 36,261IDU 1011 (8) 33,245Latino 1822 (15) 26,744African-American 1825 (15) 26,404*(p<0.001 by Kruskal-Wallis test) in mean CVL by treatment history, race/ethnicity, age, gender, HIV transmission risk category, insurancestatus, and clinical status. Source: Das et al, 2010
  14. 14. KEY ELEMENTS IN SELECTING INTERVENTIONSStep 1: Evidence- based + Feasible + Scalable + Has shown efficacy Cost Leverage Maximize in reducingeffective all + 3rd party + acquisition and/or resources payer transmission of HIV Identify priority interventions to optimize health outcomes for PLWHA and avert new HIV infectionsStep 2: Identified Compare to data Allocate interventions on current efforts additional and identify gaps resources to 14 efforts
  15. 15. SAN FRANCISCO INDICATORS MSM IDU TFSM (59,909) (18,942) (1,064) HIV- HIV+ HIV- HIV+ HIV- HIV+ (46,244) (13,565) (14,820) (4,122) (659) (405)Free Condoms 79% 70% 67% 69% 76% 84%Free Needles 76% 97%Individual 11% 16% 17% 16% 41% 41%counselingGroup 5% 11% 8% 16% 38% 40%counseling 15 Source: SF National HIV Behavioral Surveillance Project; Transfemale Needs Assessment; and 2011 HIV Consensus Estimates
  16. 16. PREVENTION INDICATORS, 2004-2011 49,789 0.9 0.81 46,101 46,101 0.8 0.75 0.75 0.78 0.7 37,394 0.73 0.72 34,997 34,518 0.6 0.59 0.5 28,285 0.55 0.58 27,806 0.4 26,368 0.3 9,834 0.2 8,605 0.16 5,532 0.14 0.09 0.1 0.06 0.08 4,917 0.07 0 3,688 4,302 MSM1 MSM2 MSM3 Free Condoms Individual Session Group Session NP Test p6m NP Test p12m# of men reached red= all MSM, blue all non-HIV+ MSM, Population denominator based on 16mean estimate for entire period Source: SF National HIV Behavioral Surveillance Project
  17. 17. SAN FRANCISCO INDICATORSParameters 2004-5 (%) 2008-9 (%)Among MSM, HIV Test in Last 12 mos. 65 71Among TFSM, HIV Test in Last 12 mos. NA 61 (2010)HIV-Positive People Unaware of Status 24 17 (15-20) % NOT tested past Testing deficit, 6Populations At risk pop. size* 6 mos.** mos.MSM 46,244 54% 24,972IDU 15,020 58% 8,712TFSM 659 63% 415Min. total additional tests needed every 6 months 34,099 17 Source: SF National HIV Behavioral Surveillance Project; Transfemale Needs Assessment; and 2011 HIV Consensus Estimates: and SF HIV Surveillance
  18. 18. SAN FRANCISCO INDICATORS 2009 2010 Total 3M 6M 3M 6M 3M 6MTotal 112(89%) 117 (93%) 131 (92%) 135 (95%) 243 (91%) 252 (94%)New HIV+ 50 (93%) 51 (94%) 57 (95%) 58 (97%) 107(94%) 109(96%)Known HIV+ 62 (86%) 66 (92%) 74 (90%) 77(94%) 136 (88%) 143 (93%) 18 Source: HIV Epidemiology Section, SFDPH
  19. 19. SAN FRANCISCO INDICATORS 2007 2008 2009 3M 6M 3M 6M 3M 6MTotal 142 (65%) 160 (73%) 103 (64%) 116 (68%) 95 (61%) 105 (67%)New 128 (65%) 143 (72%) 98 (65%) 109 (73%) 85 (60%) 92 (65%)HIV+Known 14 (64%) 17 (77%) 5 (46%) 7 (64%) 10 (67%) 13 (87%)HIV+ 19 Source: HIV Epidemiology Section, SFDPH
  20. 20. MEDIAN COUNT OF INITIAL CD4 COUNTPopulations in US Median Initial CD4 Cell Counts (cells/μL)Total 182White 239Other/Unknown 180African American 175 Below 350Hispanic/Latino 160Asian/Pacific Islander 225 CDC HIV Surveillance Supplemental Report, Volume 16, Number 1Populations in San Francisco Median Initial CD4 Cell Counts (cells/μL)Total 388White 426 Below 500Other/Unknown 464African American 351Latino 328 ~350 or belowAsian/Pacific Islander 319 20 SFDPH HIV Epidemiology 2010 Annual Report
  21. 21. MAJOR GAPS IN THE IMPLEMENTATION CASCADE: COMPARING US DATA TO SAN FRANCISCO120% United States (Gardner, et al. CID 2011) 100%100% United States (Cohen, et al. MMWR 2011) 79% 80% 80% San Francisco (SF Dept of Public Health, 2009)*80% 68% 62% 59%60% 57% 51% 47% 40% 41%40% 36% 32% 28% 24% 19%20% 0% * SF data is preliminary – Not for distribution. SFDPH HIV Epidemiology & Surveillance 03/2012
  22. 22. SHOULD AIDS BE RENAMED “ACQUIRED INFLAMMATORY DISEASE SYNDROME”? • Untreated HIV disease is associated with increased T cell activation/inflammation • Treatment dramatically reduces inflammation • The degree of residual inflammation during HAART is determined in part by CD4 nadir (strong effect < 200)THE VIRUS IS MORE TOXIC THAN THE MEDICATIONS 22 Slide courtesy of Steve Deeks
  23. 23. UNIVERSAL OFFER OF ART ON WARD 86 AND ALL SFDPH COMMUNITY HEALTH CLINICS (2010)“All patients, regardless of CD4 count, will be evaluated for initiation of antiretroviral therapy (ART)... While randomized controlled evidence for patients with higher CD4 counts is not yet available, well-designed retrospective and cohort studies support benefit in these patients. ” Decision to start ART made by the individual in conjunction with their provider 23 Modified from slide courtesy of Brad Hare, SFGH Community Forum
  24. 24. THE DATA2000 IS IN!20092001 2012 Source: al Sadr CROI 2012
  25. 25. WHERE WE WANT TO BE…120% and where we are in SF100% 100% 100% 100% 100% 100% 80%80% 68%60% 57% 51% 47%40%20% 0% HIV diagnosis Linked to Care Retained in On ART Undetectable Care VL * SF data is preliminary – Not for distribution. SFDPH HIV Epidemiology & Surveillance 03/2012
  26. 26. HIV PREVENTION PRIORITIZED STRATEGIES & INTERVENTIONS HIV Status Health Education and Prevention With Awareness Risk Reduction Positives• Routine HIV Testing • Syringe Access and • Treatment Adherence in medical settings Disposal Services • Engagement in care• Community Based • Condom Availability • STD, Viral HIV Testing (with and Program Hepatitis, and TB without pretest • Holistic Health Screening and counseling) Models Treatment• Linkage to care • Interventions to • Disclosure and• Partner Services address drivers of Partner Services HIV • Linkage to Ancillary Services Structural Changes 26 Source: HIV Prevention Plan
  27. 27. BEHAVIORAL CHANGE STILL PLAYS A CRITICAL ROLE IN THE COMPREHENSIVE APPROACH 27
  28. 28. METRICS TO EVALUATE SF’s CONTINUUM OF PREVENTION, CARE AND TREATMENT Time to Virologic Suppression Testing Diagnosis Primary Care Treatment  Virologic Suppression Linkage Engagement Engagement HIV / Retention / Retention Primary Prevention Efforts CD4 Linked to CD4 at ART Engaged Virologic Durable • Condoms, at HIV Care within initiation in Care Suppression Virologic • Syringes diagnosis 3 Mo. of Dx Suppression • Reduction in drivers of HIV Time to ART InitiationNBHS and other study results Surveillance Individual Population 28
  29. 29.  Bold and candid conversations are needed at all levels Jurisdictions are going to have to make tough choices This is not simply about how much more money a jurisdiction will need. If you scale one activity up, another must be scaled down This is not about implementing the same protocols and interventions. You will need to identify new models of services. Jurisdictions are going to have to maximize the use of their surveillance and clinical data“Do the best you can until you know better. Thenwhen you know better, do better.” Maya Angelou
  30. 30. ACKNOWLEDGMENTSPeople living with HIV/AIDS in San FranciscoSFDPH UCSF and PHP-Ward 86 at SFGHTaylor Maturo, Moupali Das, Priscilla Chu, Diane Havlir, Brad Hare, Steve Deeks,Glenn-Milo Santos, Susan Scheer, Willi Diane JonesMcFarland, H. Fisher Raymond, Tracey White House Office of National AIDS PolicyPacker, Dara Geckeler, Stephanie Cohen, Greg Millet, Jeff Crowley, Grant ColfaxNicholas Moss, Noah Carraher, SusanPhilip, Erin Antunez, Tomas Aragon,Barbara Garcia

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