The Global Epidemics
p
of HIV
among MSM in 2010: Epidemiology,
R
Responses,
and
d Human
H
Rights
Ri ht
The Global Forum on MSM & HIV Pre
Pre-Conference
Conference
July, 17th 2010, Vienna
Chris Beyrer MD, MPH
The Center for Public Health and Human Rights
Where are we in 2010?
Epidemiology:
p
gy
Ongoing epidemics among MSM in multiple LMIC Newly reported epidemics in unstudied areas
Newly reported epidemics in unstudied areas
“Resurgent” epidemics among MSM in high income countries
Responses:
Inadequate coverage and access for prevention, treatment, and care
Inadequate “toolkit” of prevention services for MSM
Human Rights:
Multiple advances in LGBT rights awareness, community empowerment, advocacy
Major “pushback” on MSM/LGBT and the human rights effort The Epidemics
Global Epidemiology of HIV in MSM in LMIC
Reviewed HIV prevalence, incidence among MSM risks for HIV coverage of services and
MSM, risks for HIV, coverage of services, and barriers to accessing health care and prevention services
prevention services
Reviewed evidence around the combined risk Reviewed
evidence around the combined risk
of injecting drug use among MSM in IDU‐driven HIV epidemics
HIV epidemics
M th d
Methods:
Systematic search:
Systematic
search: systematic
systematic methodology used to search databases methodology used to search databases
including PubMed, EMBASE, EBSCO, and the Cochrane Database of Systematic Reviews through January 30th, 2010.
‐ MeSH terms:"Homosexual, Men” OR “Homosexual”; “Human Immunodeficiency Virus”; "Primary Prevention"; "Secondary Prevention"; "Tertiary Prevention"; “Cost Analysis”, “Cost Effectiveness”. El t i l b l
Electronic global consultation
lt ti : done in October, 2009 to obtain information on epidemiology, rights contexts, and programming for MSM ‐ Used dedicated listserves in Asia, Africa, Latin America and the Caribbean, and Eastern Europe, including the amfAR MSM Initiative, the MSM Global dE t
E
i l di th
fAR MSM I iti ti th MSM Gl b l
Forum, UNDP, and UNAIDS. F
Face to Face consultation t F
lt ti (Bangkok, Feb. 2010) with key informants from (
k k b
)
hk
f
f
28 countries to obtain country specific data
Search Protocol and Results: Systematic Review on the HIV Epidemic among MSM in LMIC. 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.
status
(n=503)
Conference abstracts
retrieved for further
y ((n=61))
analysis
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 C
Census B
Bureau D
Database
t b
ffor
HIV/AIDS (n=2)
--Beyrer, et al, Epi Reviews, 2010
133 p
prevalence studies
from 130 unique reports:
data from 50 countries
Studies retrieved
that were
coordinated by
EuroHIV and
commissioned by
European Union
(n=16)
Algorithm: Development of the Epidemic Scenarios
Algorithm: Development of the Epidemic Scenarios
HIV prevalence in any high-risk
subgroup >5%
Unavailable Data
HIV prevalence ratio (MSM/gen pop)
Ratio ≥ 10
Ratio < 10
HIV prevalence ratio (IDU/gen pop)
Ratio < 10
HIV prevalence ratio (IDU/gen pop)
Ratio ≥ 10
Ratio ≥ 10
Ratio < 10
% population IDU
SCENARIO 3
< 1%
≥ 1%
% population MSM
< 10%
SCENARIO 1
SCENARIO 4
SCENARIO 2
--Beyrer et al, Epi Revs, 2010
MSM risks are the predominant exposure mode for HIV infection
in the population: Scenario 1
Country
Ecuador
Peru
Bolivia
Uruguay
Argentina
Colombia
Paraguay
Brazil
Honduras
Panama
Guatemala
El Salvador
Nicaragua
M i
Mexico
Jamaica
Ghana
Aggregate HIV Prevalence
among MSM
15.1%
13.8%
21 2%
21.2%
18.9%
12.1%
19.4%
13.0%
%
8.2%
9.8%
10.6%
11 5%
11.5%
7.9%
9.3%
25 6%
25.6%
31.8%
25%
(12.8-17.4)
(13.4-14.3)
(17 6 24 7)
(17.6-24.7)
(16.1-21.7)
(10.8-13.4)
(17.2-21.6)
(6.2-19.9)
((6.9-9.4))
(8.1-11.5)
(6.7-14.6)
(6 7 16 4)
(6.7-16.4)
(4.8-10.9)
(4.8-13.7)
(24 8 26 5)
(24.8-26.5)
(25.4-38.3)
(20.5-29.5)
Population
Prevalence
Rate (15+)
HIV prevalence
among MSM vs
Gen Pop
0.27%
0.37%
0 13%
0.13%
0.38%
0.40%
0.51%
0.48%
0.50%
%
0.57%
0.83%
0 70%
0.70%
0.77%
0.20%
0 26%
0.26%
1.38%
1.67%
55.9
37.3
163 1
163.1
49.7
30.3
38.0
27.1
16.4
17.2
12.8
16 4
16.4
10.3
46.5
98 5
98.5
23.0
15.0
Scenario 1
MSM is the predominant exposure in HIV transmission MSM
is the predominant exposure in HIV transmission
General population rates low to very low
Scenario 1
Scenario
1 Peru
HIV 0.5% General Adult
Prevalence 13.8% MSM
13.8% MSM
Brazil
0.6% General Adult 8.2% MSM
8.2% MSM
Taxonomy
Gay,
Bisexual,
Transvestite/ transsexual
MSW
Heterosexual, married
Some dual risk of sex work and IDU; other substance use
other substance
Other factors
Homosexual/gay
Bisexual
Transgendered/Transvestite
MSW
Heterosexual
Sex work and transactional sex, other substance use sex with women
substance use,
sex with women
SCENARIO1
MSM are the predominant exposure group for HIV
MSM are the predominant exposure group for HIV Beyrer C, et al, Epidemiology Reviews, 2010.
Scenario 2
Same sex risks in the context of established HIV epidemics among IDU: Eastern Europe and Central Asia; HIV risk among MSM is generally not well accepted, response focused on IDU
Scenario 2:
Scenario
2: Ukraine
HIV 1.6% General Adult Prevalence 11.0% MSM
40.1% IDU
Russia
1.1% General Adult 3.4% MSM
3.4% MSM
11.8% IDU Taxonomy
Homosexual, Heterosexual, Bisexual
Homosexual,
Bisexual,
Heterosexual
Other factors
Other factors
Small proportion of dual MSM Small
proportion of dual MSM
IDU risk; transactional sex with other males; Bisexual practices
Small proportion of dual of MSM IDU Small
proportion of dual of MSM IDU
risk; Sex with women, marriage common; Transactional sex
SCENARIO 2: Same sex behavior is evaluated in the context of established HIV epidemics among IDU
t bli h d HIV id i
IDU
Beyrer C, et al, Epidemiology Reviews, 2010.
S
Scenario
i 3
Same sex risks in the context of high prevalence and mature HIV epidemics among heterosexuals: Sub‐Saharan Africa
Scenario 3
Scenario
3 Kenya
HIV 6.1% General Adult Prevalence 15.2% MSM
Prevalence 15.2% MSM
Malawi
11.5% General Adult
21.4% MSM
Taxonomy
Homosexual/gay (basha or shoga), Bisexual, Heterosexual
T
Transgendered persons
d d
Homosexual/gay
Bisexual, heterosexual
Other factors
High rates of sex with women, bisexual Sex work, transactional sex, bisexual and concurrent bisexual concurrency, some dual MSM
bisexual and concurrent bisexual concurrency, some dual MSM‐IDU
IDU risks
risks
practices; Possible dual MSM IDU risk; Other substance use
MSM risks occur in the context of mature and widespread HIV epidemics among heterosexuals
Country
Aggregate HIV Prevalence
among MSM
Population
Prevalence
Rate (15+)
HIV prevalence
among MSM vs
Gen Pop
Namibia
12.4%
(8.1-16.8)
13.32%
0.9
Botswana
19.7%
(12.5-26.9)
21.56%
0.9
South Africa
15.3%
((12.4-18.3))
15.89%
1.0
Zambia
32.9%
(29.3-36.6)
15.72%
2.1
Kenya
15.2%
(13.3-17.2)
7.49%
2.0
Tanzania
12.4%
(9.5-15.2)
5.88%
2.1
Malawi
21.4%
(15.7-27.1)
11.46%
1.9
Nigeria
13 5%
13.5%
(12 0-15 )
(12.0-15.)
2 88%
2.88%
47
4.7
Sudan
8.8%
(7.1-10.4)
1.26%
7.0
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.
S
Scenario
i 4
MSM, heterosexual, and IDU transmission all contribute significantly to the HIV MSM,
heterosexual, and IDU transmission all contribute significantly to the HIV
epidemic
SScenario 4
i 4 Thailand
Th il d
HIV 1.55% General Adult P
Prevalence
l
23 0% MSM
23.0% MSM
IIndia
di
0.3% General Adult
14 5% MSM
14.5% MSM
Taxonomy
Katoey – transgendered; puchai
transgendered; puchai ‐
homosexual with masculine features and behavior; Heterosexual; Bisexual (seua bi)
Male sex workers
Kothi – receptive partner; Panthi
receptive partner; Panthi –
penetrative partner; Double‐decker –
both penetrative and receptive partner
Hijras – recognized third gender; identify as women and prefer receptive Other factors
Male sex work common (can be
associated with migration); other drug use‐ mostly meth
Stigma, discrimination, and violence are significant barriers; Variable IDU SCENARIO 4: MSM, heterosexual, and IDU t
transmission all contribute significantly to the HIV epidemic i i
ll
t ib t i ifi tl t th HIV id i
Beyrer C, et al, Epidemiology Reviews, 2010.
Responses
Prevention and Treatment
Prevention and Treatment
Grading Interventions
Grade Level Strength of
Recommendation
Grade 1
Strong
Grade 2a
Probable
Grade 2b
Possible
Grade 2c
Pending
Grade 3
Insufficient
Grade 4
Inappropriate
Explanation
•
•
•
Efficacy is Consistent
Bi l i ll plausible
Biologically
l
ibl
Consensus from community sources
•
•
•
•
•
Limited Efficacy Data
Bi l i ll Plausible
Biologically
Pl
ibl
Efficacy is inconsistent
Biologically plausible
Consensus from community sources
•
•
•
•
•
•
Ongoing Definitive Trials
Biological Plausibility
Inconsistent Data
Undefined Biologic Plausibility
Consistent data demonstrating lack of efficacy
Consensus from Community Sources of
I
Inappropriate
i t Intervention
I t
ti
Combination HIV Prevention
f MSM:
for
MSM
Combination prevention model we are using has 3 components, 1 b
d l
h
added in IDU contexts
Outreach with condom and lubricant promotion and distribution
Community level behavioral interventions
ARVs
For MSM IDU: harm reduction and substitution therapy
Using the Goals Model
•
Goals is a deterministic model that uses data to project HIV prevalence and incidence: uses demography; sexual behavior; HIV and STI rates
and STI rates
•
We have refined the model by including:
•
Divided “MSM intervention” into separate parameters: 1. outreach with condom promotion and distribution
2. community level behavioral interventions
3. Inclusion of ARV and new findings on efficacy of ARV in couples (Donnell D, et al, Lancet 2010)
couples (Donnell D, et al, Lancet
•
Expanded risk categorization for MSM to low, medium, and high risk, and MSM IDU
i k d MSM IDU
Predicting impact on HIV spread
Estimates the number of ALL new HIV infections for 4 selected countries: Peru Ukraine Kenya Thailand
Peru, Ukraine, Kenya, Thailand
•
Null: both MSM interventions and ARV for general population dropped from 2007 to zero
•
Current: most recent coverage levels of MSM interventions and ARVs continue at same level to 2015
•
100% coverage of MSM: MSM preventive interventions incrementally 100%
coverage of MSM: MSM preventive interventions incrementally
increase from last reported level to 100% by 2015, ARVs increase to estimated level in which all MSM would be covered •
For epidemics with IDU components (Scenarios 2 and 4), modeled combined impact of 100% coverage of MSM and 60% coverage of IDU
Results
Scenario 1: Impact of MSM interventions
on all new HIV infections in Peru
Null
Current
100% MSM interventions
Peru modeling outcomes: combined prevention for MSM Much higher coverage of interventions for MSM will be needed to change the trajectory of HIV
will be needed to change the trajectory of HIV 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 interventions on
all new HIV infections in Ukraine, from 2008 forward
41
40
T
Thousands
39
38
37
36
35
34
2008
2010
Null
Current
2012
2014
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 modeling outcomes: U
a e ode g outco es:
combined prevention for MSM Higher coverage of interventions for MSM would have an impact on the HIV epidemic in Ukraine
have an impact on the HIV epidemic in Ukraine Combinations with IDU and MSM interventions have the greatest impact
have the greatest impact
Scenario 3: Impact of MSM interventions
y
on all new HIV infections in Kenya
Null
Current
100% MSM interventions
Scenario 3: Impact of MSM interventions
on all new HIV infections, from 2008 forward
125
120
115
Thousands
110
105
100
95
90
85
80
75
2008
Null
2010
Current
2012
2014
100% MSM interventions
Kenya modeling outcomes: e ya ode g outco es:
combined prevention for MSM Even where the HIV prevalence is high and mature among the general population, MSM specific interventions positively impact the p
p
y p
general population
While relative impact is modest, the numbers of infections averted are considerable
Scenario 4: Impact of MSM interventions Scenario
4: Impact of MSM interventions
on all new HIV infections in Thailand Null
Current
100% MSM interventions
SScenario 4: Impact of MSM and IDU interventions i 4 I
t f MSM d IDU i t
ti
on all new HIV infections in Thailand
Null
Current
100% MSM interventions 100% MSM + 60% IDU
SScenario 4: Impact of MSM and IDU interventions i 4 I
t f MSM d IDU i t
ti
on all new HIV infections in Thailand
45
40
Thousands
35
30
25
20
15
2008
Null
2010
Current
2012
2014
100% MSM interventions 100% MSM + 60% IDU
Thailand modeling outcomes
Thai epidemic is stable overall
Higher levels of coverage for MSM with existing interventions would lead to i ti i t
ti
ld l d t
overall declines in HIV epidemic
p
Substantial increases in coverage of IDU Substantial
increases in coverage of IDU
interventions have major impact on the HIV id i
HIV epidemic
Modeling the impact of MSM M
d li
h i
f MSM
interventions and ARVs
interventions and ARVs • MSM specific interventions (community‐based b h i l d di ib i
behavioral and distribution of condoms and lubricants) f
d
dl b i
)
impact new infections among MSM and general population but
l i b must include access to ARVs for MSM
i l d
ARV f MSM
• Benefits seen in 4 / 4 epidemic scenarios
Benefits seen in 4 / 4 epidemic scenarios
• Where
Where IDU plays a role in the epidemic, major impacts IDU plays a role in the epidemic, major impacts
among the general population can be seen when coverage of needle exchange and substitution therapy
coverage of needle exchange and substitution therapy are increased Where are we going?
Where are we going?
• Access to prevention, treatment, and care for MSM is a fundamental human right
g
• These findings suggest that increasing h
fi di
h i
i
coverage and access for these men is also a key component of the overall response to HIV
• The science and the rights based‐approaches are in agreement
Acknowledgements
Center for Public Health and Human Rights, Johns Hopkins Global HIV/AIDS Program
The World Bank
•
•
•
•
•
•
•
•
•
•
Chris Beyrer MD, MPH
Frangiscos Sifakis, PhD, MPH
Andrea Wirtz MHS
Andrea Wirtz, MHS
Stefan Baral MD, MPH
Damian Walker, PhD, Msc
Benjamin Johns, MPA
Futures Institute
Futures Institute
•
•
John Stover, PhD
Lori Bollinger, PhD
Robert Oelrichs, MD, PhD, MPH
Iris Semini, PhD
Laith Abu Raddad PhD
Laith Abu‐Raddad, PhD
David Wilson, PhD