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. IN 2006 THE HEADLINES SAID:
“Pluto Not a Planet,
Astronomers Rule”

3. REACTIONS TO THE INFORMATION!
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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-Champion
Forensic 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. Population Health And Prevention
SF Health Department and Affiliated Clinics
SFDPH manages and implements a robust portfolio of HIV research and works in
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collaboration with academic, clinical and community partners

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
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Source: Nieves-Rivera, 2010

7. SAN FRANCISCO’S APPROACH TO MAXIMIZING THE
CONTINUUM OF PREVENTION, CARE AND TREATMENT
Primary
HIV Surveillance
Prevention
Efforts Testing Diagnosis Primary Care Treatment
Virologic HIV
Suppression
• PrEP, PEP,
condoms,
syringes Linkage Engagement Engagement
• Drivers / Retention / Retention
1. Substance
use
2. Alcohol
3. Meth
4. Crack Routine Mental Health Treatment
Adherence
Medical Services
5. Poppers
6. 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. 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. GREATEST RISK FOR ACQUISITION OF HIV
AND UNAWARE OF HIV STATUS
Greatest 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 HIV
Greatest Disparities:
• White MSM
• African American MSM
• Latino MSM
• TFSM
Unaware 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. HIV IS ENDEMIC IN SF
4500
Gay men/MSM: Endemic
4000
3500 Injection drug users: Endemic
3000
2500 Heterosexuals: Neither
2000 epidemic nor endemic
1500
1000
500
0
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2007
2008
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Source: McFarland, 2009

11. DRIVERS OF HIV IN SF
Driver: An underlying condition that is directly linked to a large
number of new HIV infections in San Francisco
Prevalence 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. IDENTIFY THE VIRAL BURDEN
IN POPULATIONS
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Source: Das, et al. 2010

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) 64,160
Not on treatment 2924 (23) 40,056
Not engaged in care 4637 (37) 36,992
MSM-IDU 1791 (14) 36,261
IDU 1011 (8) 33,245
Latino 1822 (15) 26,744
African-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, insurance
status, and clinical status.
Source: Das et al, 2010

14. KEY ELEMENTS IN SELECTING
INTERVENTIONS
Step 1: Evidence-
based
+ Feasible + Scalable +
Has shown efficacy
Cost Leverage Maximize in reducing
effective all + 3rd party + acquisition and/or
resources payer transmission of HIV
Identify priority interventions to optimize health outcomes for
PLWHA and avert new HIV infections
Step 2: Identified Compare to data Allocate
interventions on current efforts additional
and identify gaps resources to
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efforts

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%
counseling
Group
5% 11% 8% 16% 38% 40%
counseling
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Source: SF National HIV Behavioral Surveillance Project; Transfemale Needs Assessment; and 2011 HIV Consensus Estimates

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
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mean estimate for entire period Source: SF National HIV Behavioral Surveillance Project

17. SAN FRANCISCO INDICATORS
Parameters 2004-5 (%) 2008-9 (%)
Among MSM, HIV Test in Last 12 mos. 65 71
Among 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, 6
Populations At risk pop. size*
6 mos.** mos.
MSM 46,244 54% 24,972
IDU 15,020 58% 8,712
TFSM 659 63% 415
Min. total additional tests needed every 6 months 34,099
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Source: SF National HIV Behavioral Surveillance Project; Transfemale Needs Assessment; and 2011 HIV Consensus Estimates: and SF HIV Surveillance

18. SAN FRANCISCO INDICATORS
2009 2010 Total
3M 6M 3M 6M 3M 6M
Total 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%)
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Source: HIV Epidemiology Section, SFDPH

19. SAN FRANCISCO INDICATORS
2007 2008 2009
3M 6M 3M 6M 3M 6M
Total 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+
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Source: HIV Epidemiology Section, SFDPH

20. MEDIAN COUNT OF INITIAL CD4 COUNT
Populations in US Median Initial CD4 Cell Counts (cells/μL)
Total 182
White 239
Other/Unknown 180
African American 175
Below 350
Hispanic/Latino 160
Asian/Pacific Islander 225
CDC HIV Surveillance Supplemental Report, Volume 16, Number 1
Populations in San Francisco Median Initial CD4 Cell Counts (cells/μL)
Total 388
White 426 Below 500
Other/Unknown 464
African American 351
Latino 328 ~350 or below
Asian/Pacific Islander 319
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SFDPH HIV Epidemiology 2010 Annual Report

21. MAJOR GAPS IN THE IMPLEMENTATION CASCADE:
COMPARING US DATA TO SAN FRANCISCO
120%
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. 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
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Slide courtesy of Steve Deeks

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
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Modified from slide courtesy of Brad Hare, SFGH Community Forum

24. THE DATA
2000 IS IN!
2009
2001
2012 Source: al Sadr CROI 2012

25. WHERE WE WANT TO BE…
120%
and where we are in SF
100% 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. 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
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Source: HIV Prevention Plan

27. BEHAVIORAL CHANGE STILL PLAYS A CRITICAL ROLE
IN THE COMPREHENSIVE APPROACH
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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 Initiation
NBHS and other
study results
Surveillance
Individual Population
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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. Then
when you know better, do better.” Maya Angelou

30. ACKNOWLEDGMENTS
People living with HIV/AIDS in San Francisco
SFDPH UCSF and PHP-Ward 86 at SFGH
Taylor Maturo, Moupali Das, Priscilla Chu, Diane Havlir, Brad Hare, Steve Deeks,
Glenn-Milo Santos, Susan Scheer, Willi Diane Jones
McFarland, H. Fisher Raymond, Tracey White House Office of National AIDS Policy
Packer, Dara Geckeler, Stephanie Cohen, Greg Millet, Jeff Crowley, Grant Colfax
Nicholas Moss, Noah Carraher, Susan
Philip, Erin Antunez, Tomas Aragon,
Barbara Garcia