Transcript Slide 1

THE GLOBAL EPIDEMICS OF HIV
AMONG MSM IN 2010
EPIDEMIOLOGY, RESPONSES, AND HUMAN RIGHTS
RESULTS OF A PROJECT SUPPORTED BY THE WORLD BANK
Stefan Baral MD MPH FRCPC
Johns Hopkins School of Public Health, USA
Overview
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
Introduction
Know your epidemic
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Epidemiology of HIV among MSM
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Epidemic Scenarios of HIV among MSM
Burden of Disease
Risk Factors for Disease
Know your Response
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Combination HIV Prevention Interventions for MSM
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Using GOALS Model to Predict HIV Epidemics with varying levels of coverage
of preventive services for MSM

The role of Human Rights in Responding to HIV
Conclusions
Introduction
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Epidemiology
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Responses
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Ongoing epidemics among MSM in multiple LMIC
Newly identified epidemics in previously unstudied areas
Resurgent epidemics among MSM in high income countries (HIC)
Inadequate coverage and access for prevention, treatment, and care
Inadequate “toolkit” of prevention services for MSM
Human Rights:
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Multiple advances in LGBT rights awareness, community empowerment,
activism
Major “pushback” on MSM/LGBT and rights effort
Epidemiology
Potentially relevant studies
identified and abstracts screened
for retrieval from international
conference searches (n=819)
Potentially relevant studies identified
and abstracts screened for retrieval
from literature Searches (n=1612)
Duplicates Studies
excluded (n=255)
Reports excluded based on
abstract due to lack of
quantitative data,
geographical context,
sample size, self-reported
HIV status.
(n=1434)
Abstracts excluded based on
abstract due to lack of
quantitative data, geographical
context, sample size, self-reported
HIV status.
(n=503)
Conference abstracts
retrieved for further
analysis (n=61)
Full texts retrieved for further
analysis with QUOSA (n=178)
Reports excluded based on
lack of HIV prevalence data,
inability to calculate country
population HIV prevalence
(n=111)
Abstracts excluded based on
inability to find background data on
specific country HIV prevalence,
inability to find further information
on statistical methods (n=8)
Unique studies retrieved from
US Census Bureau Database for
HIV/AIDS (n=2)
--Beyrer, et al, Epi Reviews, 2010
133 prevalence studies
from 130 unique reports:
data from 50 countries
Studies retrieved
that were
coordinated by
EuroHIV and
commissioned by
European Union
(n=16)
Epidemic Scenarios for MSM
Evidence suggested four epidemic scenarios for LMIC MSM epidemics
-Scenario 5 will come from MENA region: now largely “unavailable data”
Beyrer C, et al, Epidemiology Reviews, 2010.
Scenario 1 - MSM risks are the predominant exposure
mode for HIV infection in the population
40.00%
H
30.00%
I
V
P
r
e
20.00%
v
a
l
e
n
c
10.00%
e
0.00%
Aggregate MSM Prevalence
General Population Prevalence
SCENARIO1
MSM are the predominant exposure group for HIV
Beyrer C, et al, Epidemiology Reviews, 2010.
Scenario 2- MSM risks occur within established HIV
epidemics driven by injecting drug use (IDU)
50.00%
H
I
V
P
r
e
v
a
l
e
n
c
e
40.00%
30.00%
Aggregate IDU
Prevalence
Aggregate MSM
Prevalence
20.00%
General Population
Prevalence
10.00%
0.00%
Poland
Serbia
Armenia
Georgia
Moldova
Russia
East Timor
Ukraine
SCENARIO 2: Same sex behavior is evaluated in the context of
established HIV epidemics among IDU
Beyrer C, et al, Epidemiology Reviews, 2010.
Scenario 3 - MSM risks occur in the context of mature
and widespread HIV epidemics among heterosexuals
30.00%
H
I
V
P
r
e
v
a
l
e
n
c
e
20.00%
Aggregate
MSM
Prevalence
10.00%
General
Population
Prevalence
HIV Prevalence
among Men
(15-49)
0.00%
SCENARIO 3: Same sex behavior is evaluated in the context of high
prevalence and mature HIV epidemics among heterosexuals
Beyrer C, et al, Epidemiology Reviews, 2010.
SCENARIO 4: MSM, heterosexual, and IDU
transmission all contribute significantly to the HIV epidemic
30%
H
I
V
P
r
e
v
a
l
e
n
c
e
20%
Aggregate MSM
Prevalence
10%
General
Population
Prevalence
0%
SCENARIO 4: MSM, heterosexual, and IDU
transmission all contribute significantly to the HIV epidemic
Beyrer C, et al, Epidemiology Reviews, 2010.
EPIDEMIC SCENARIOS: Unavailable Data
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Algeria
Azerbaijan
Belarus
Djibouti
Iran
Iraq
Jordan
Kazakhstan
130 other Countries
• Kyrgyzstan
• Lebanon
• Libya
• Morocco
• Syria
• Tunisia
• West Bank and Gaza
Assessment of Data Quality
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Disease burden among MSM in LMIC
 Nearly
 Tells
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all data is prevalence data from convenience samples
us where epidemic was and not where it is going
 May not be generalizable to general population of MSM
 Samples are among young MSM—so likely very conservative
estimates of disease burden
HIV Incidence has been characterized in cohort studies in Kenya, Peru,
Brazil
Individual Risk factors for MSM
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Unprotected anal intercourse ( risk with receptive UAI)
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High frequency of male partners (>3 sexual contacts/ week)
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High number of lifetime male partners (>10)
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Injection drug use
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Alkyl Nitrate (poppers)
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Methamphetamines
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Lack of Circumcision (for predominantly insertive MSM with
female partners)
Beyrer, C. STD, 2007
Mediated through increased
sexual exposure
Ecological Model for HIV Risk in MSM
Level of Risks
Stage of Epidemic
Public Policy
Community
Network
Individual
Source: Baral and Beyrer, 2006
HIV among MSM in High Income Countries
Source: Sullivan, et al, 2009. Reemergence of the HIV Epidemic Among Men Who Have Sex With Men in North
America, Western Europe, and Australia, 1996–2005
Number of newly diagnosed HIV infections among men who have sex
with men, Hong Kong, Singapore, Taiwan and Japan, 2002 - 2007
TaiwanJapan
Hong KongSingapore
HK
SG
TW
JP
56
38
305
50
54
336
340
67
94
503
449
96
101
584
514
118
108
743
571
168
145
1075
690
Source: van Griensven, Baral, et al. 2009. The Global Epidemic of HIV Infection among Men who have Sex with Men. Current Opinion in HIV/AIDS
Know Your Response
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There is a dearth of data characterizing effective HIV
prevention interventions for MSM in Low and Middle Income
Countries
Systematic review completed of HIV prevention data for MSM
in Low and Middle Income Countries as well as Global
Consultation of Community Best Practices
Data was evaluated to assess current state of evidence for
interventions to assess benefit
To respond to multiple levels of HIV risk among MSM,
combination prevention must be multi-level and multimodal
A modified Grade approach for HIV
preventive interventions
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Grading Evidence
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3 Primary Parameters
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Efficacy Data
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Biological Plausibility
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Community Best Practices
6 Grades
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Strong
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Probable
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Possible
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Pending
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Insufficient
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Inappropriate
Combination HIV Prevention Interventions for MSM (CHPI)
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CHPI Includes
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Behavioural Interventions
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Biomedical Interventions
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Increasing condom and lubricant use during sex
Biomedical interventions aim to decrease transmission and acquisition risk of
but don’t decrease prevalence of risk practices
Structural Interventions
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These have rarely been appropriately evaluated likely because of
complexity in study design to characterize efficacy and effectiveness of these
interventions
GRADE Level
Strength of Recommendation
•Decriminalization
•Government-sponsored anti-homophobia policy
•Mass media engagement
•Religious and Traditional Leader Engagement
•Male engagement programs
•Community systems strengthening
•Health Sector Interventions
Grade 1
Strong
Prevention Expenditures for MSM
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Concentrated Epidemics
 MSM
are one of predominant risk groups (Epidemic
Scenario 1, 2, 4)
 3.3%
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of total expenditures supporting MSM
Generalized Epidemics (Epidemic Scenario 3)
 Emerging
 0.1%
evidence of risk among MSM
of total expenditures supporting MSM
Source: Global HIV Prevention Working Group: Global HIV Prevention: The Access, Funding, and Leadership Gaps. 2009
Prevention Expenditures - Asia
24,000,000.00
U 21,000,000.00
S
D
18,000,000.00
E
q
u 15,000,000.00
i
v
a 12,000,000.00
l
e
n 9,000,000.00
t
Total HIV Prevention
Expenditure
MSM Share of Prevention
Expenditure
(
2
0
0
4
6,000,000.00
)
3,000,000.00
0.00
Thailand
Vietnam
Cambodia
China
Lao
Source: USAID, HIV Expenditure on MSM Programming in the Asia-Pacific Region., 2006
Prevention Expenditures – Latin America
Peru
Source: Medición del gasto en sida: avances y retos de la respuesta latinoamericana al VIH.
ONUSIDA. 2010
Predicting impact of interventions on incidence and
prevalence levels
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Estimates the number of ALL new HIV infections with and without interventions for
4 different epidemic scenarios: Peru, Ukraine, Kenya, Thailand
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Null: both MSM interventions and ARV for general population dropped
from 2007 levels to zero
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Current: most recent coverage levels of MSM interventions and ARVs
continue at same level to 2015

100% coverage of MSM: MSM interventions incrementally increase from
last reported level to 100% by 2015, ARVs increase to estimated level in
which all MSM would be covered
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For epidemics with IDU components (Scenarios 2 and 4), modeled combined
impact of 100% coverage of MSM and 60% coverage of IDU
Using the Goals Model
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Goals is a deterministic model that uses data to
project HIV prevalence and incidence: uses
demography; sexual behavior; HIV and STI rates
 We have refined the model by including
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Separated “MSM intervention” to separate
parameters
Expanded risk categorization for MSM to low,
medium, and high risk, and MSM IDU
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High Risk: Male sex workers
Medium Risk:> 1 male sex partner in last 12 months
Low Risk:
0 – 1 male sex partner in last 12 months (stable relationship)
MSM IDU:
Men who report same sex practices and inject drugs
Source: Bollinger, L. How can we calculate the ‘‘E’’ in ‘‘CEA’’? AIDS 2008, Futures Institute
Scenario 1: Impact of MSM interventions
on all new HIV infections in Peru
Null
Current
100% MSM interventions
Peru
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Modeling outcomes: combined prevention for MSM
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Markedly higher coverage of interventions for MSM will
be necessary to change trajectory of HIV epidemic in
Peru
Scenario 2: Impact of MSM interventions on
all new HIV infections in Ukraine
Null
Current
100% MSM interventions
Scenario 2: Impact of MSM and IDU interventions on
all new HIV infections in Ukraine
Null
Current
100% MSM interventions 100% MSM + 60% IDU
Ukraine
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Modeling outcomes: combined prevention for MSM
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Higher coverage of interventions for MSM has impact on
the HIV epidemic in Ukraine
Combinations with IDU interventions have the greatest
impact on the HIV epidemic
Scenario 3: Impact of MSM interventions
on all new HIV infections in Kenya
Null
Current
100% MSM interventions
Scenario 3: Impact of MSM interventions
on all new HIV infections in Kenya
125
120
115
Thousands
110
105
100
95
90
85
80
75
2008
Null
2010
2012
Current
100% MSM interventions
2014
Kenya
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Modeling outcomes: combined prevention for MSM
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Even where the HIV prevalence is high and mature
among the heterosexual population, MSM specific
interventions positively impact the general population
Scenario 4: Impact of MSM interventions
on all new HIV infections in Thailand
Null
Current
100% MSM interventions
Scenario 4: Impact of MSM and IDU interventions
on all new HIV infections in Thailand
Null
Current
100% MSM interventions 100% MSM + 60% IDU
Thailand
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Modeling outcomes: combined prevention for
MSM
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Thai epidemic is stable overall
Higher levels of coverage for MSM with existing
interventions would lead to overall declines in HIV
epidemic
Substantial increases in coverage of IDU interventions
have major impact on the HIV epidemic
Modeling the impact of MSM interventions and ARVs
Key messages
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MSM specific interventions (community-based behavioral
and distribution of condoms and lubricants) impact new
infections among MSM and general population but must
include access to ARVs for MSM
Benefits may be seen even in varying epidemic scenarios
Where IDU plays a role in the epidemic, the greatest
impact among the general population can be seen when
coverage of needle exchange and substitution therapy
are increased as well
Human Rights Contexts
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Methods
 Health
Impact Assessment of criminalization of samesex practices as a risk factor for HIV among MSM
 Participatory methods in selected case study countries
including Malawi, Uganda, and Senegal
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Results
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Increased enforcement of laws criminalizing same sex practices have
resulted in widespread fear and hiding and interfered with the ability to
provide HIV prevention, care, and treatment services
These arrests have also interfered with the ability of MSM to seek
evidence-based HIV services resulting in increased HIV risk
Conclusions
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HIV continues to disproportionately affect MSM in high and low
income settings
There are both Individual and Structural risk factors for HIV infection
To improve the health outcomes of MSM in low and middle income
settings, a comprehensive effort is needed:

Know your Epidemic by
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Generating high quality epidemiologic data to
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characterize populations
demonstrate need
inform prevention strategies
Know your Response by
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Adopting comprehensive prevention strategies that address multiple levels of risk
Appropriately resourcing prevention programs for MSM in response to attributable
fraction of HIV disease
Acknowledgements
Global HIV/AIDS Program
The World Bank
Center for Public Health and Human
Rights, Johns Hopkins

Robert Oelrichs, MD, PhD, MPH

Chris Beyrer MD, MPH

Iris Semini, PhD

Frangiscos Sifakis, PhD, MPH

Laith Abu-Raddad, PhD

Andrea Wirtz, MHS

David Wilson, PhD

Damian Walker, PhD

Benjamin Johns, MHA
The Futures Institute


John Stover, PhD
Lori Bollinger, PhD
Know your Epidemic and Response
Session Team

Shiv Khan, OBE

Zoryan Kis

Andy Seale

Rob Carr

Joel Nana

Nyambura Njoroge

Maria Prins, Allison Talan