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SOCIAL AND STRUCTURAL FACTORS ASSOCIATED WITH HIV RISK AMONG FEMALE SEX WORKERS (FSW) AND MEN WHO HAVE SEX WITH MEN (MSM) IN SWAZILAND, 2011 Stefan Baral, MD MPH, JHSPH

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Social and Structural Factors associated with HIV Risk among Female Sex Workers (FSW ) and Men who have Sex with Men (MSM) in Swaziland, 2011. Stefan Baral, MD MPH, JHSPH. Overview. Background HIV Epidemiology among MSM and FSW Objectives Methods Results Quantitative Qualitative - PowerPoint PPT Presentation

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Page 1: Stefan Baral, MD MPH, JHSPH

SOCIAL AND STRUCTURAL FACTORS ASSOCIATED WITH HIV RISK AMONG FEMALE SEX WORKERS (FSW) AND MEN WHO HAVE SEX WITH MEN (MSM) IN SWAZILAND, 2011

Stefan Baral, MD MPH, JHSPH

Page 2: Stefan Baral, MD MPH, JHSPH

Overview Background

HIV Epidemiology among MSM and FSW Objectives Methods Results

Quantitative Qualitative

Conclusions

Page 3: Stefan Baral, MD MPH, JHSPH

HIV Epidemiology UNAIDS Classifies Epidemics as:

Low level Less than 5% Prevalence in any high risk group

Concentrated Greater than 5% in any high risk group, but less

than 1% antenatal clinics Generalized

Greater than 1% in antenatal clinics

Page 4: Stefan Baral, MD MPH, JHSPH

Global HIV Prevalence

UNAIDS. Global Update on the HIV Pandemic. 2010

IDU, SW

IDU, MSM, SW,

HCHC

Legend• IDU Injection Drug Use• SW Sex Work• HC High Risk

Heterosexual Transmission

Page 5: Stefan Baral, MD MPH, JHSPH

Legend

2002200320042005200620072008

Senegal [77]

21.5%(463)

21.8%(501)

Ghana [11]

25.0%(N/A)

Nigeria [79]

13.4%(1,125) Sudan [86]

9.3%(713)

7.3%(406)

Kenya [78]

24.6%(285)

Tanzania [80]

12.3%(509)

Malawi [81,82]

21.4%(201)

Soweto [83]

28.9%(249)

Botswana [82]

19.7%(117)

30.9%(68)

Capetown (Township) [84]Capetown

[85]

10.6%(538)

Namibia [82]

12.4%(218)

Egypt [90]

6.2%(267)

HIV Prevalence among MSM in Africa

Source: van Griensven, Baral, et al. The Global Epidemic of HIV Infection among Men who have Sex with Men. Curr Opinion on HIV/AIDS, 2009

Page 6: Stefan Baral, MD MPH, JHSPH

Systematic Review of HIV among FSW

Page 7: Stefan Baral, MD MPH, JHSPH

Data Quality Disease burden among MARPS in Africa

Data is predominantly Prevalence Data from Convenience Samples Tells us where epidemic was and not where it is going May not be generalizable to general population of MARPS

Samples are among young people--likely very conservative estimates of disease burden

Compared against age standardized data (15-49) in general population

HIV Incidence has been characterized in cohort studies in Kenya ~ 10% Incidence among MSM and FSW

Prevalence of Same-Sex Practices/Sex work are unknown in most of Africa Potential Risk Misclassification?

Page 8: Stefan Baral, MD MPH, JHSPH

Ecological Model for HIV Risk in MSM

Stage of Epidemic

Individual

CommunityPublic Policy

Network

Level of Risks

Source: Baral and Beyrer, 2006

Page 9: Stefan Baral, MD MPH, JHSPH

Quantitative Study Goal To collaborate with MOH to develop a

comprehensive set of data that can be used by municipal and national government in Swaziland to design evidence-based HIV prevention programs for Most at Risk Populations.

Page 10: Stefan Baral, MD MPH, JHSPH

Specific Aims Calculate a probability estimate of HIV and

Syphilis prevalence among sex workers and men who have sex with men in Swaziland

Describe behavioral factors associated with HIV/STI infection, including individual sexual practices, the composition of sexual networks, concurrent partnerships, substance use, and access to clinical health care and prevention services

Examine the role of social and structural factors on HIV-related behaviors and risk for HIV infection among sex workers and MSM including social inclusion, stigma and discrimination

Page 11: Stefan Baral, MD MPH, JHSPH

Methods Target Populations

328 Men who have had anal sex with another man in the last 12 months

325 women who report sex work as primary form of income

Accrual Methodology Respondent-driven sampling

Behavioral Survey Validated and Piloted in each population

Biological Testing HIV and Syphilis Swaziland National Guidelines with Pre and Post-test

counseling

Page 12: Stefan Baral, MD MPH, JHSPH

Respondent-Driven Sampling Peer-referral system using coupon

management system that allows for adjustment for network sizes and homophily (the concept that people recruit people that are similar to themselves)

Allows for estimation of unbiased estimates from a non-probability sample

Page 13: Stefan Baral, MD MPH, JHSPH

FSW DemographicsNo. %

Age<21 64 19.721-24 82 25.225-29 91 2830+ 88 27.1Total 325 100

EducationPrimary or less 106 32.6Some Secondary 175 53.8Completed Secondary or more 44 13.5Total 325 100

Marital statusMarried 3 0.9Cohabiting 10 3.1Divorced/Sep 23 7.2Single/Never married 285 88.8Total 321 100

Number of childrenNone 80 24.61 100 30.82+ 145 44.6Total 325 100

Has other income sourceNo 216 66.7Yes 108 33.3Total 324 100

Page 14: Stefan Baral, MD MPH, JHSPH

Numbers of PartnersNumber of new clients (past 30 days)*0-1 44 13.52-4 142 43.75-10 108 33.2>10 31 9.5Total 325 100

Number of regular clients (past 30 days)*0-1 27 8.32-4 93 28.65-10 131 40.3>10 74 22.8Total 325 100

Number of non-commercial partners (past 30 days)None 37 11.41 172 52.92+ 116 35.7Total 325 100

Disclosed occupation to    Family member 98 30.2Health care worker 84 25.9

Page 15: Stefan Baral, MD MPH, JHSPH

Condom UseAlways used condoms with new clients in past monthNo 77 25.8Yes 222 74.2Total 299 100

Always used condoms with regular clients in past monthNo 160 51.8Yes 149 48.2Total 309 100

Always used condoms with non-commercial partners in past monthNo 189 66.5Yes 95 33.5Total 284 100

Always used condoms with all reported partners in past monthNo 247 76.5Yes 76 23.5Total 323 100

Condom break/slip with any partner in past monthNo 143 44.7Yes 177 55.3Total 320 100

Page 16: Stefan Baral, MD MPH, JHSPH

Structural Risks for HIVCharacteristic No.

Percentage

Have ever been raped 123 39.2Instances of rape since age 18 0 6 4.6  1-2 77 58.3  3-4 17 12.9  5-6 9 6.8  6 or more 23 17.4Responsible for rape

Uniformed Officer (police, military, security) 4 3.9  Family Member 21 20.6  Regular partner (not client) 14 13.7  One-time client 33 32.4  Regular Client 7 6.9As a result of selling sex:

Felt afraid to seek healthcare 143 44.0  Experienced legal discrimination 152 46.8  Been refused police protection 160 49.4  Been blackmailed 113 34.8  Verbal and physical harassment 198 60.9  Have been tortured 173 53.2  Have been beaten up 125 38.7 Have been beaten up by  Uniformed Officers (police, miltary, security) 45 20.8  Family Member 21 9.7  Regular Partner 16 7.4  One time client 11 5.1  Regular client, partner 9 4.2  Manager/pimp 6 2.8

Page 17: Stefan Baral, MD MPH, JHSPH

HIV Prevalence among FSW compared to Reproductive Age Women, Swaziland 2011

Source: Central Statistical Office & Macro International, 2008, p. 222

16-20 21-24 25-29 30-400

10

20

30

40

50

60

70

80

90

FSW HIV PrevalenceFemale HIV Prevalence

Age Groups

HIV

Pre

vale

nce

(%)

Page 18: Stefan Baral, MD MPH, JHSPH

Significant Univariate Associations with HIV among FSW Higher Age Lower Education Marriage Ever Pregnant

Page 19: Stefan Baral, MD MPH, JHSPH

MSM Demographics Characteristic Crude prevalence (N)

Age 15-19 20-24 25-29 30-34 35 -39 40-44

 22.0 (71)48.0 (155)20.4 (66)5.6 (18)2.5 (8)1.5 (5)

Age Below 25 25 or older

 70.0 (226)30.0 (97)

Marital status Single Married

 96.9 (310)3.1 (10)

Education Some secondary school Completed secondary school Vocational training College/university

 32.1 (101)43.5 (137)4.1 (13)20.3 (64)

Sexual orientation Gay/homosexual Bisexual Heterosexual

 63.3 (205)35.2 (114)1.5 (5)

Page 20: Stefan Baral, MD MPH, JHSPH

Sexual Practices Characteristic Crude prevalence

(N)Always Wear Condoms with Regular Partners YesNo

  50.6 (157)49.4 (266)

Had both male and female sexual partners in the last 12 monthsYesNo

37.4 (122)62.6 (204)

Had a concurrent regular partnership with two or more regular partners in the last 12 months No Yes male and female Yes, two or more male partners Yes, two or more female partners

  45.5 (148)20.9 (68)31.1 (101)2.1 (7)

Exchange sex in the last 12 months 26.1 (85)Number of male partners in the last 12 months 1 2-5 6 or more

 32.9 (107)58.5 (190)8.6 (28)

Page 21: Stefan Baral, MD MPH, JHSPH

Condom Use Characteristic Crude prevalence (N)

STI testing in the last 12 months 13.0 (41)HIV testing in the last 12 months No Yes, once Yes, more than once

 45.7 (149)30.4 (99)23.9 (78)

Access to condoms No access Difficult or little access Some access Very easy access

 0.9 (3)17.9 (58)11.4 (37)69.8 (226)

Access to lube No access Difficult or little access Some access Very easy access

 26.7 (83)30.2 (94)15.4 (48)27.6 (86)

Received HIV prevention for MSM last 12 months

27.1 (88)

Page 22: Stefan Baral, MD MPH, JHSPH

Structural Risks for HIV Characteristic Crude

prevalence (N)

Afraid to seek health care due to sexuality 55.3 (177)

Felt rejected by friends due to sexuality 54.4 (176)

Faced legal discrimination due to sexuality 31.2 (100)

Ever been raped 6.0 (19)

Ever been to prison 12.9 (42)

Ever beaten up due to sexuality 9.0 (29)

Page 23: Stefan Baral, MD MPH, JHSPH

HIV Prevalence among MSM compared to Reproductive Age Men, Swaziland 2011

16-20 21-24 25-29 30-400

10

20

30

40

50

60

MSM HIV PrevalenceMale HIV Prevalence

Age Groups

HIV

Pre

vale

nce

(%)

Source: Central Statistical Office & Macro International, 2008, p. 222

Page 24: Stefan Baral, MD MPH, JHSPH

Significant Univariate Associations with HIV among MSM Age Syphilis Been in Prison Excessive Alcohol Use

Page 25: Stefan Baral, MD MPH, JHSPH

Positive Prevention 30 years into the HIV epidemic, new infections still

outpace people initiating treatment Historically, most HIV prevention interventions

targeted uninfected individuals Globally, little access to HIV testing Fear of blaming the victim and adding to stigma

Recently, dramatic scale-up of HIV testing and treatment services worldwide More PLHIV now know their status With treatment, PLHIV living longer, healthier lives

Positive prevention helps people living with HIV lead a complete and healthy life and reduce the risk of transmission of the virus to others.

Page 26: Stefan Baral, MD MPH, JHSPH
Page 27: Stefan Baral, MD MPH, JHSPH

WHO guidelines In 2007, WHO issued

guidelines for positive prevention interventions in resource-limited settings

However, little evidence from studies focused on PLHIV, and little focus on MARPS

Page 28: Stefan Baral, MD MPH, JHSPH

Study goal To examine the prevention needs of Most

at Risk Populations (MARPS) including Sex Workers (SW) and Men who have Sex with Men (MSM) in Swaziland to better tailor PHDP programs for these populations.

Page 29: Stefan Baral, MD MPH, JHSPH

Study Methods Qualitative study design One-on-one, in-depth interviews with key

stakeholders (n=16) and HIV-positive SW (n=21) and MSM (n=20) Most MSM and SW interviewed twice each

for more depth Focus groups with SW (n=3) and MSM

(n=3)

Page 30: Stefan Baral, MD MPH, JHSPH

Data analysis Weekly interviewer debriefing meetings All interviews audio recorded, transcribed, and

translated into English Full day data analysis workshop held Oct. 13, 2011

at the Mountain Inn Attended by representatives from MSM and SW groups,

MOH and NERCHA staff, interviewers and members of the research team, clinicians, and others

Read transcripts, developed list of key themes, and discussed implications

Further coding of transcripts and analysis by 4 study team members

Page 31: Stefan Baral, MD MPH, JHSPH

Stigma, discrimination, and violence

Both groups experienced dual stigma related to both HIV+ and SW/MSM identities Led to lack of disclosure of both identities

SW reported violence from clients and police Some clients became violence when asked to use condoms Others would refuse to pay after sex and become violent Police round-ups, demand for sex, violence

MSM reported discrimination and violence from a wide range of individuals Partners, families, general public, police raids

Both groups felt they had no recourse to bring such incidents to the authorities

Page 32: Stefan Baral, MD MPH, JHSPH

Risk cycle of hunger, sex work, and HIV for SW

SW described a risk cycle of hunger & poverty driving sex work driving HIV infection.

HIV in turn drives an increased need for ‘healthy foods’

Sex work leads to alienation from social networks which offer material and emotional support against hunger & poverty.

Hunger &

poverty

Sex work

HIV infectio

n

Increased need

for healthy foods

Reduced social support

Page 33: Stefan Baral, MD MPH, JHSPH

Challenges keeping MSM/SW PLHIV physically healthy

Perceived stigma from health care settings leading to lack of care-seeking

Perceived stigma from families/partners leading to lack of disclosure of HIV status Challenges with ART adherence, hiding

medications, lack of social support for treatment Poverty and hunger

For SW, risk cycle of hunger, sex work, and HIV MSM also reported transactional sex, challenges

adhering to ART, and challenges getting to clinic due to poverty and hunger

Page 34: Stefan Baral, MD MPH, JHSPH

Challenges keeping MSM/SW PLHIV mentally healthy

Primary challenge of living with dual stigma

Depression and self-stigma or shame Some MSM said feelings of self-stigma

led MSM to drink alcohol to “forget”, which often led to sexual risk behavior

Page 35: Stefan Baral, MD MPH, JHSPH

Challenges preventing further HIV transmission

Questions around HIV prevention during clinical services often assume heterosexuality/one partner Due to fear of stigma, SW/MSM often just answer the

question asked (e.g., ‘I don’t have a steady partner’), rather than discuss their true risk behaviors – missed opportunity for prevention

SW offered more money for sex without condoms Clandestine nature of MSM relationships may lead to

more and more casual partnerships MSM described many of their partners as bisexual or having

female partners/wives (possibly to hide MSM behavior or to fulfill cultural expectations)

MSM relationships are kept secret and therefore families do not play a role in relationship counseling and peacekeeping

Page 36: Stefan Baral, MD MPH, JHSPH

Successes preventing further HIV transmission Sex workers appreciated the tailored HIV

educational sessions provided for them MSM suggested ‘training of trainers’ model

Train trusted MSM community members who could then share messages with others

Both SW and MSM suggested continued/further distribution of condoms and particularly lubricant to prevent condom breakage

Consider MSM/SW “expert clients” for those living with HIV

Page 37: Stefan Baral, MD MPH, JHSPH

Challenges increasing agency of MSM/SW PLHIV

Dual stigma and hidden identities MSM/SW have difficulty trusting

outsiders until they get to know particular individuals over time

MSM/SW are often unwilling to disclose their status publically to represent these groups in HIV-related activities

Page 38: Stefan Baral, MD MPH, JHSPH

Successes increasing agency of MSM/SW PLHIV Ongoing activities by MOH, PSI, SNAP,

SWAPOL, and others – including this research – suggests if approached in the right way, MSM and SW are interested in participating in HIV prevention, care and treatment decisions for their communities

Page 39: Stefan Baral, MD MPH, JHSPH

Service delivery models Some respondents suggested developing

special clinics or services for HIV+ MSM or SW Others said targeted services would reinforce

stigma Several participants said health care workers

should be trained on issues related to MARPS “I would train health care workers. Even their

procedures manuals should have information on how to handle MARPS … Also let’s make educational materials that also speak of MARPS.” – KI

Page 40: Stefan Baral, MD MPH, JHSPH

Successful existing models of SW-friendly services

Respondents emphasized the success of specific SW-friendly services (e.g. FLAS, others)

Several said the “support group” code word model used for SW-friendly services in Piggs Peak, Lobamba, and a few other clinics worked well. “For instance, Piggs Peak and Lobamba, they come and say,

‘I’ve come to see so and so … and the health care worker will know it’s from the support group so it means she is a sex worker. Same with Lobamba, they meet and she can say, ‘I’m from the support group,’ oh, then she will know she is a sex worker without announcing.” – KI

“We could use some of those centres as learning sites, you know. We could share the lessons learnt from those people.” – KI

Page 41: Stefan Baral, MD MPH, JHSPH

“They are human beings, they are Swazi.”

Key informants consistently said that regardless of personal belief, they had an ethical responsibility to provide services to everyone, equally “As a health sector, my belief is non-discriminatory

services to all the members of the population, and issues of legality and everything rest with the Ministry of Justice.” – KI

“Even though I don’t approve of what they are doing … as a public health officer, I have to make sure that they have access to health services. I don’t have to judge them. I don’t have to give my views on what they are doing. But my duty is to make sure that they have access to services… whatever their sexual orientation is, they are human beings, they are Swazi.” – KI

Page 42: Stefan Baral, MD MPH, JHSPH

Conclusions FSW and MSM represent distinct high risk populations in

Swaziland These populations are underserved with only sporadic targeted

program Even in the context of countries with hyperendemic HIV prevalence

rates, there is still concentration of HIV risk and prevalence Moving Forward

Combination HIV Prevention Programs Biomedical

Increasing HTC and Active Linkage to ART for eligible Evaluate future strategies as they are developed

Chemoprophylaxis Behavioral

Increasing Condom and Condom Compatible Lubricant Use Structural

Community Systems Strengthening Health Sector Interventions Gender normalization strategies Safe work spaces

Page 43: Stefan Baral, MD MPH, JHSPH

Next steps for Studies Finalize findings and recommendations with MOH Write final report Swaziland dissemination to MOH, MARPS

technical working group, stakeholders, media Global dissemination through peer-reviewed

articles and presentations for the International AIDS Conference, July 2012

Compare with same qualitative research in the Dominican Republic (concentrated HIV epidemic)