Populations / Interventions Committee: Final Recommendations

1. Populations / Interventions Committee:Final Recommendations HPPG Full Body Meeting 29 June 2005

2. HPPG Greg Braxton Beau Gratzer Don Hermann Juliet Jones Lloyd Kelly Mark Morante Kathleen Neville Valerie Pang Marcus Randall Valerie Richards CDPH Nanette Benbow Demian Christiansen Robert Fireall Jose Gonzalez Dave Kern Esther Moreno Nik Prachand P / I Committee Membership

3. P/I Committee Purpose • Identify population groups with the highest HIV incidence rates (high-risk negatives) and HIV / AIDS prevalence rates (PLWHIV / AIDS) • Identify interventions that are most effective at reducing HIV transmission / acquisition in high-risk populations • Identify geographic areas with the highest HIV incidence rates (“hot spots”)

4. P/I Committee Guiding Questions • Who are those most at risk for acquiring HIV infection? • Who are those most at risk for infecting others with HIV? • What interventions are most effective at reducing individuals’ risk for acquiring / transmitting HIV? • Where are cases of new HIV infection occurring in the City?

5. P/I Committee Goals • Targeting resources to population groups at highest-risk for being infected and populations groups at highest-risk of infecting others • Recommending interventions that have the greatest potential to impact high-risk behavior and to encourage individuals to know their HIV status • Targeting resources to geographic areas with the highest HIV incidence rates

6. Full Body Considerations • Define and give text definition to geographic boundaries • HIV data are reported by zip code. Given the Committee’s charge to identify areas with highest HIV incidence, zip codes with high incidence were used and clustered as appropriate. • Gap Analysis: consider trends and shifts • Trends and shifts in epidemiological data will be monitored by HPPG throughout the implementation cycle, i.e., 2007-2009. If necessary, priorities will be revised.

7. Full Body Considerations • “Unidentified” risk may be attributed to funding cuts, social marketing campaign shifts and stigma • While a host of barriers may affect the collection of HIV case data, the unknown / unidentified cases do not impact the epidemiological data in a significant way. See slides later in the presentation.

8. Full Body Considerations • Zip code of testing vs. zip code of risky behavior • Actually, the zip codes represent where an individual who tests HIV+ lives, not the testing site or site of high-risk behavior. Testing site locations can be highly variable and don’t necessarily say much about the high-risk population / area. Locations where high-risk behaviors take place are also variable and impractical to enumerate. Should a location of high-risk behavior be known, the Committee and CDPH would encourage funded agencies to target individuals there even if the location falls outside the zip code of residence.

9. Full Body Considerations • Where are the heterosexual men being captured in terms of DEBI and testing? • HRH men, like all potential populations, were equally considered in the epidemiological data. The data clearly demonstrate that high-risk heterosexual sex, as a behavior, is not the mode of transmission most linked to new or living male HIV cases, i.e., men are being infected via other behaviors. See slides later in the presentation. • HIV prevention needs of people over 50 & 60 • The Special Projects Committee considered this population.

10. P/I Committee Process • Received a presentation on DEBI from HATU • Received an “EPI 101” presentation from the Office of HIV / AIDS Surveillance (OHAS) • Considered a model of the natural history of HIV infection • Reviewed current HIV and AIDS incidence and prevalence data and other relevant data • Received intervention presentations from the HIV Prevention Program • Using HIV case data, modeled the epidemic in the City to identify high-risk negative populations, high-risk positive populations and geographic “hot spots” • Identified appropriate interventions, including DEBI, for populations

11. Populations—High-Risk Negatives • Who are those most at risk for acquiring HIV infection? • Who are those most at risk for infecting others with HIV? • What interventions are most effective at reducing individuals’ risk for acquiring / transmitting HIV? • Where are cases of new HIV infection occurring in the City?

12. Recent HIV Diagnoses, Chicago, 2002-2003 WHO ARE THOSE MOST AT RISK OF ACQUIRING HIV INFECTION? What are their demographic characteristics? What are their risk-factors? Where do they live? Look for similarities and differences…

13. HIV Incidence Data • Recent HIV infections = HIV incidence data • Incidence defined: Number of HIV cases in 2003 Population (of Chicago) * 1 year = 1,119 New HIV Cases in 2003 2,896,016 * 1 year = 0.00038639289 or 38.64 per 100,000 (per year)

14. Natural History of HIV Infection* Progression to AIDS HIV Infection Mortality High Risk Behavior HIV Incidence AIDS Incidence Late-testers AIDS Incidence & Late-testers HIVIncidence Mortality At Risk Living with HIV Living with AIDS Died

15. Populations—High-Risk Negatives • HIV incidence data were considered across several levels • Zip Code • Gender • Race / Ethnicity • Age • Mode of Transmission • Together, these variables illuminate the highest-risk HIV-negative populations in the City (for the P/I Committee, highest-risk means HIV incidence rate > City rate)

16. Populations—High-Risk Positives • Who are those most at risk for acquiring HIV infection? • Who are those most at risk for infecting others with HIV? • What interventions are most effective at reducing individuals’ risk for acquiring / transmitting HIV? • Where are cases of new HIV infection occurring in the City?

17. LIVING HIV CASES, Chicago WHO ARE THOSE AT RISK OF TRANSMITTING HIV INFECTION? What are their demographic characteristics? What are their risk-factors? Where do they live? Look for similarities and differences…

18. Populations—High-Risk Positives • Living HIV infections = Prevalent HIV / AIDS cases • HIV / AIDS prevalence data were considered across several levels • Zip Code • Gender • Race / Ethnicity • Age • Mode of Transmission

19. Populations—High-Risk Positives • To determine those MOST AT RISK of transmitting HIV, another factor needed to be considered: RISK HIERARCHY • In short, risk hierarchy looks at the relative potential for efficiently transmitting HIV. Risk Hierarchy looks at both specific activities and specific behavioral risk groups (BRG). • Risk Hierarchy describes the scientific basis for HIV transmission.

20. Activity Relative Risk Sharing unsterile needles 12 Unprotected receptive anal intercourse 9 Unprotected receptive vaginal intercourse 3 Unprotected anal insertive intercourse 2 Unprotected insertive vaginal intercourse 1.5 Giving unprotected fellatio 1 Giving unprotected cunnilingus 0.5 Getting unprotect fellatio 0.1 Getting unprotected cunnilingus 0.1 Risk Hierarchy—Specific Activity From the 2000 Washington D.C. HIV Prevention Plan, p. 5.3 / 1997 San Francisco HIV Prevention Plan

21. Population Relative Risk IDU and MSM / IDU 5 MSM 4 HRH Female 3 HRH Male 2 Risk Hierarchy—BRG From 2001-2003 State of Florida HIV/AIDS Comprehensive Plan, p. 94

22. So What Does Risk Hierarchy Say About Those MOST AT RISK for Transmitting HIV in Chicago? • Efficient means of HIV transmission contributing to new HIV infections include: • Needle / syringe sharing • Male-to-male sexual transmission • Male-to-female sexual transmission • Therefore, populations living with HIV who engage in these behaviors are MOST AT RISK for transmitting HIV.

23. Populations—Incidence vs. Prevalence • How do HIV incidence and HIV / AIDS prevalence data compare across levels? • Overall, incidence and prevalence data show a similar picture with respect to zip code, gender, race / ethnicity and mode of transmission. • HIV / AIDS prevalence data show an older population than do HIV incidence data. Youth are less represented in HIV / AIDS prevalence data.

24. Populations—Intervention Location (Zip Codes) • Where’s the appropriate place to intervene with high-risk populations? • Zip Code data show where individuals testing positive LIVE, not where individuals test or where individuals engage in high-risk behavior. • Testing sites are highly variable within high-risk populations. • High-risk environments are also highly variable and impossible to enumerate. • HIV prevention efforts should address the needs of high-risk populations not only in their home zip code, but also in the places where they engage in high-risk behavior, i.e., service providers should know the population they serve.

25. Populations—Unknown Cases • What should we know about unknown cases? • Unknown is not a new mode of transmission. • Unknown reflects the following: • Not documented by provider • Not asked • Not discussed • Reviewed 256 HIV cases with no identified risk; followed these to see how they were redistributed after 12 months • 124 (48%) were still NIR • 87 (34%) were redistributed • 45 (18%) dropped out of our dataset

26. Populations—Reallocation of Unknowns Before Re-allocation After Re-allocation (Maximum Estimates) MSM 45% IDU 14% MSM/IDU 2% Hetero 13% Other 2% Unknown 24% MSM 50% IDU 15% MSM/IDU 2% Hetero 17% Other 2% Unknown 14% Apply re-allocation proportions NOTE: The distribution of HIV cases by mode of transmission changes only slightly and does not make a considerable difference in the priority setting process or alter the P / I committee’s conclusions.

27. Populations—Decision-Making Model • The Committee used the data to create a model that identifies: • Areas (zip codes) with highest HIV incidence • Populations at high-risk for acquiring / transmitting HIV within these areas • The model collapses like categories where possible.

28. P/I Committee Guiding Questions • Who are those most at risk for acquiring HIV infection? • Who are those most at risk for infecting others with HIV? • What interventions are most effective at reducing individuals’ risk for acquiring / transmitting HIV? • Where are cases of new HIV infection occurring in the City?

29. Zip Code Clusters

30. Zip Code Clusters

31. Cluster A Male 90% (654/727) Hispanic 17% (108/654) AA 23% (153/654) White 55% (357/654) MSM 73% (79/108) IDU 14% (22/153) MSM 63% (96/152) MSM 87% (311/357) 25-39 MSM 75% (59/79) 25-39 MSM 6154% (52/96) 40+ MSM 34% (33/96) 25-39 MSM 56% (174/311) 40+ MSM 40% (123/311) Male Hispanic MSM 25-39 F and M AA/H/W IDU 25-50+ Male AA MSM 25-50+ Male White MSM 25-50+ Indicates priority population living with HIV/AIDS

32. Zip Code Clusters

33. Cluster B-Male Male 70% (528/763) Hispanic 23% (122/528) AA 55% (292/528) White 19% (100/528) MSM 53% (65/122) IDU 18% (21/122) IDU 29% (86/292) MSM 37% (107/292) MSM 77% (77/100) 25-39 MSM 48% (31/65) 40+ MSM 40% (26/65) 40+ IDU 77% (66/86) 25-39 MSM 56% (43/77) 40+ MSM 43% (33/77) 13-24 MSM 22% (23/107) 25-39 MSM 59% (63/107) 40+ MSM 20% (21/107) Male Hispanic MSM 25-50+ F and M AA/H/W IDU 25-50+ Male AA MSM 13-24+ Male AA MSM 25-50+ Male White MSM 25-50+ Indicates priority population living with HIV/AIDS

34. Cluster B-Female Female 30% (235/763) Hispanic 14% (33/235) AA 80% (188/235) IDU 24% (8/33) IDU 24% (45/188) HRH 45% (75/188) 25-34 IDU 31% (14/45) 40+ IDU 64% (29/45) 13-24 HRH 24% (18/75) 25-39 HRH 48% (36/75) 40+ HRH 28% (21/75) F and M AA/H/W IDU 25-50+ Female AA HRH 13-24 Female AA HRH 25-50+ Indicates priority population living with HIV/AIDS

35. Zip Code Clusters

36. Cluster C Female 36% (211/580) Male 64% (368/580) AA 93% (196/211) AA 87% (322/368) HRH 40% (77/196) IDU 17% (33/196) IDU 21% (67/322) MSM 48% (154/322) 13-24 HRH 18% (14/77) 25-39 HRH 60% (46/77) 40+ HRH 22% (17/77) 13-24 MSM 19% (29/154) 25-39 MSM 60% (92/154) 40+ MSM 21% (33/154) 25-39 IDU 39% (13/33) 40+ IDU 61% (20/33) 25-39 IDU 19% (13/67) 40+ IDU 81% (54/67) Female AA HRH 13-24 Female AA HRH 25-50+ F and M AA/H/W IDU 25-50+ Male AA MSM 13-24 Male AA MSM 25-50+ Indicates priority population living with HIV/AIDS

37. P/I Committee Guiding Questions • Who are those most at risk for acquiring HIV infection? • Who are those most at risk for infecting others with HIV? • What interventions are most effective at reducing individuals’ risk for acquiring / transmitting HIV? • Where are cases of new HIV infection occurring in the City?

38. Taking a big step back… • INTERVENTIONfrom the root INTERVENE • INTERVENEfrom the Latin INTERVENIRE • INTERbetween, among • VENIREcome • INTERVENIREto come between • INTERVENEto come or occur between two things, events or points in time…so as to hinder or alter an action • INTERVENTIONthe action, idea, thing, etc. that comes or occurs between…

39. HIV Prevention Intervention— A Definition • A specific activity (or set of related activities) intended to reduce HIV risk • In a particular target population • Using common strategy for delivering the prevention messages • With distinct process and outcome objectives, and • A protocol outlining steps for implementation

40. Interventions • Interventions were considered for each identified high-risk negative and high-risk positive population. Interventions included those from: • CDC Evaluation Guidance • Compendium • DEBI (Diffusion of Evidence-Based Interventions) • Other science-based literature

41. Interventions—Process • Committee reviewed sources • Committee selected interventions that had the greatest potential to reduce HIV infection / transmission

42. Interventions—EG/C/Other Lit • Evaluation Guidance, Compendium and other science-based interventions include: • Individual Level Interventions (ILI) • Prevention Case Management (PCM) • Group Level Interventions (GLI) • Needle / Syringe Exchange Programs (N / SEP) • Outreach (OR) • Health Communication / Public Information (HC / PI) • Community Level / Social Marketing (CL / SM)

43. Interventions—EG/C/Other Lit • The Committee omitted Community Level / Social Marketing (CL / SM) • Rationale: • CL / SM is a very complex intervention, much more than other recruitment interventions • CL / SM requires substantial resources to be conducted effectively • In the past, most projects funded to implement CL / SM actually provided HC / PI • CL will be covered by DEBI • SM will be covered by the SP Committee Special Initiatives

44. Interventions • The Committee adopted the 2002 interventions model: At least one recruitment intervention must be coupled with at least one focused intervention. RECRUITMENT FOCUSED OUTREACH HEALTH COMMUNICATION / PUBLIC INFORMATION ILI GLI PCM N / SEP

45. Interventions—EG/C/Other Lit • The Committee confirmed the following interventions for MSM, HRH and PLWHIV populations • ILI • GLI • PCM • OR • HC / PI

46. Interventions—EG/C/Other Lit • The Committee confirmed the following intervention IDU populations • N / SEP • Rationale: • N / SEP have been proven one of the most effective HIV prevention interventions available • Limited HIV prevention resources makes it essential to target high-risk populations with the most effective interventions • Considering behavior implicit in IDU, sharing needles / syringes leads to HIV infection / transmission • Understanding individuals engage in other high-risk behaviors, the Committee recommends that these behaviors be targeted, along with their associated interventions, in the appropriate categories, i.e., MSM, HRH, PLWHIV

47. Interventions—DEBI • DEBI—Diffusion of Evidence-Based Interventions • The Diffusion of Effective Behavioral Interventions (DEBI) project was designed to bring science-based, community-and group-level HIV prevention interventions to community-based service providers and state and local health departments. The goal is to enhance the capacity to implement effective interventions at the state and local levels, to reduce the spread of HIV and STDs, and to promote healthy behaviors. • www.effectiveinterventions.org

48. Popular Opinion Leader Mpowerment RAPP Safety Counts SISTA SiHLE WiLLOW Many Men, Many Voices Community PROMISE Teens Linked to Care Smart PCM Holistic Health Recovery Program Healthy Relationships Street Smart VOICES/VOCES Project Respect Partnership for Health Options Interventions—DEBI

49. Interventions—DEBI • The Committee selected the following DEBI to enhance and complement the other identified interventions: • Community PROMISE (CP) • Many Men, Many Voices (MMMV) • Popular Opinion Leader (POL) • Real AIDS Prevention Project (RAPP) • Rationale: • The Committee reviewed the recommended populations and geographic areas to ensure all populations / areas were covered • The Committee reviewed DEBI that are currently being implemented in Chicago (e.g., 04064 Directly-Funded CBOs) to identify gaps and ensure broad coverage of DEBI

50. Interventions—DEBI • The selected DEBI target the following populations: • MSM (high-risk negative and high-risk positive) • MMMV • POL • Community Promise • HRH (high-risk negative and high-risk positive) • RAPP • Community Promise • IDU (high-risk negative and high-risk positive) • Community Promise