Program Science and Sex Work: Challenges and Opportunities

James Blanchard, MD, MPH, PhDProfessor and Director

Centre for Global Public HealthUniversity of Manitoba

Program Science

• Definition:– “Promoting collaboration and integration between

programs and science to improve the ways programs are designed, implemented and evaluated to accelerate and increase health impact”

• Focuses on multiple levels:– Strategic – population focus, resource allocation– Implementation – effectiveness of intervention mix– Management / evaluation – scaling up, monitoring,

optimizing implementation

Why Focus on Sex Work?

• Sex workers among the most vulnerable groups• Key to the HIV and STI transmission dynamics in many

world regions• A key focus of HIV prevention strategies in many

countries and regions• Sex work is highly diverse and changing rapidly in

many contexts• Still much room for improvement in the coverage and

quality of programs for sex workers• Sex work is complex…

Why is more “science” needed? Key Program Questions

Priority, Scale and Macro planning

Mix of interventions components

Optimal management processes

Relative size and distribution ofSW population?

Contribution to transmissiondynamics?

Outreach models? Prioritization?Client interventions? Migration?

Structural interventions? Prioritization of new FSWs?

Economies of scale? Optimal coverage? Phases of programs?

Public vs. private sector? Role ofCBOs?

Planning and Initiation Phase

Implementation Phase

Implementation and ConsolidationPhase

Planning and Initiation Phase• Few studies that directly measure the relative size of the

FSW and/or client population:– Issues in definition– Inconsistent methods (direct vs. indirect)

• Few studies characterize the distribution of FSWs:– By typology (no accepted classification)– Urban / rural

• Relative size of the client population is usually unknown:– Problems with direct measurement

• Relative contribution of FSW to the overall epidemic is difficult to assess without these basic parameters

Karachi Lahore Faisalabad Multan0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,00011

,546

14,1

68

2,03

9

2,49

6

5,68

7

1,26

8

1,07

0

1,13

6

8,58

2

1,13

6

1,51

4

690

12,2

82

2,56

7

5,24

4

685

Size of Key Sub-Populations, By City, 2005

FSW MSW Hijra IDU

Sub-

Popu

latio

n Si

zePakistan

Karachi

Lahore

Faisalabad

Multan

0

2

4

6

8

10

12

Pakistan – Relative Size of FSW Population, per 1000 Adult Men

Karachi Lahore Faisalabad Multan0

100

200

300

400

500

600

700

219

653

31107

200

10 16 25

192

22 25 21

Estimated Total Number of Sex Partnerships per Month, x 1,000

FSW MSW Hijra

Part

ners

per

Mon

th, T

hous

ands

Pakistan – Sexual Partnerships for Key Populations in Different Cities

Distribution of FSWs in Karachi and Lahore by Main Solicitation Location, 2005

50%49%

1%

Karachi

Public PlacesHome/KKBrothel

22%

75%

3%

Lahore

Public PlacesHome/KKBrothel

Implementation: Beyond the Basics – Understanding Risk and Vulnerability

• What are the highest risk contexts?• When does HIV transmission occur?• Who are the highest risk partners?

“Payana” Research Project*

• Based on the mapping data, 142 villages with large number of migrant FSWs were selected from the 3 B districts (Belgaum, Bagalkot, Bijapur)

• The target sample size was 1,500 (900-1000 non-migrants and 500-600 migrants)

• We recruited a cohort of 1,564 women (645 migrant)• All the migrant women in the villages were selected; for the non-

migrants FSWs, a target was set for each taluka proportionate to the size of the estimated non-migrant FSWs population

• Retention rate of cohort members was >95%• Data collection via in-person interviews at baseline and 3, 9 and 15

months• Qualitative component to look in-depth at key issues

* Funded through Avahan

Main destinations of migrant FSWs

- Dark red arrows - over 30% of FSWs- Red arrows - 21 to 30% of FSWs- Orange - 11 to 20% of FSWs- Green - 5 to 10% of FSWs

- The most common destinations are Pune, Sangli, Bombay and Bhiwandi (80%), followed by Kolhapur, Miraj and Karad. - Bijapur FSWs go to Bombay, Pune and Bhiwandi. - Belgaum FSWs go to Pune, Sangli and Bombay and to a smaller extent to Miraj and Goa. - Bagalkot FSWs go to Pune, Sangli, Bhiwandi and Bombay, but also to Kolhapur, Karad and Miraj.

Migration/mobility and Client Volume

Local Mobile Migrant0

1

2

3

4

5

6

1.61.9 1.8

2.9

5.7

At OriginAt Destination

Clie

nts p

er d

ay (m

ean)

Consistent condom use at origin

Local Mobile Migrant0

10

20

30

40

50

60

70

80

90

100

85 8592

76

63

81

22

31

15

With occasional client

With regular client

With non-paying partnerPerc

ent

Consistent condom use at destination

Mobile Migrant0

10

20

30

40

50

60

70

80

90

10091

99

75

95

50

25

With occasional clientWith regular clientWith non-paying partner

HIV Prevalence among FSWs in 4 Districts in Karnataka by Duration in Sex Work

0-1 2 to 4 4 to 9 10+0

5

10

15

20

25

30

35

BaselineRound 2

Duration in Sex Work

HIV

Prev

alen

ce (%

)

Period, Cohort Analysis of sex work patterns in the first year of sex work

• Data collected at the 9 month interview from migrant FSWs

• Asked focused questions to gather information about sex work during their first year of sex work

• Stratified by year of entering sex work:– Before 1993 (n=163)– 1993-1999 (n=315)– 2000-2004 (n=297)– 2005-2008 (n=101)

Practiced Sex Work Within / Outside the Village of Origin During the First Year of SW

Before 1993 1993-99 2000-4 2005-80

10

20

30

40

50

60

70

8071.5

59.856.3

61.6

39.9

49.9 48.9

39Within VillageOutside Village

Period of Entering Sex Work

Perc

ent

Proportion of FSWs reporting that condoms were available during the first year of sex work

At Origin At Destination0

10

20

30

40

50

60

70

80

6.7

17.616.2

43.7

23.2

58.5

18.8

70.3

Before 19931993-992000-42005-8Pe

rcen

t

Proportion of FSWs reporting that found it easy to use condoms with clients within the first year

At Origin At Destination0

10

20

30

40

50

60

70

80

1.3

8.911.4

43.5

20.5

62.8

29.7

73.4

Before 19931993-992000-42005-8Pe

rcen

t

Proportion of FSWs Reporting NEVER Using a Condom During the First Year of Sex Work

At Origin At Destination0

10

20

30

40

50

60

70

80

90

10092.6

7881.6

46.8

68.4

26.4

63.4

15.6

Before 19931993-992000-42005-8Pe

rcen

t

Program Implications

• Although well-established, the program is “too late”:– Much of the HIV incidence occurs in the first year or

two, prior to program involvement• Programs are less effective at increasing condom

use early in sex work at the origin– At origin, early sex work is “home-based” and often

hidden– At destination, early sex work is usually in brothels,

with better established condom programming

What about clients?

• Programs are usually generic and indiscriminant in focus and vague in coverage

• Relative importance of client programs varies:– General power dynamics between FSWs and

clients• Relative importance of clients, regular clients

and other partners is seldom known

HIV prevalence (%) among FSW clients in 6 districts of Karnataka

Bagalkot Belgaum Bellary Bangalore Mysore Shimoga0

2

4

6

8

10

12

14

16

13.4

6.2 6.0

2.4

5.4

2.6

HIV

prev

alen

ce (%

)

Number of FSWs visited by clients in the past 6 months

Total

Belgaum

Bagalkot

Bellary

Shimoga

Bangalore Urban

Mysore

0% 20% 40% 60% 80% 100%

17

23

29

5

22

13

1

21

19

18

19

31

21

11

42

42

31

56

39

45

30

13

11

16

16

7

11

20

8

5

7

5

1

10

37

1 2-3 4-5 6-9 10+

Bagalkot – clients and lovers

• Many of the sexual partners of FSWs in Bagalkot are “regular”

• In addition, many of the FSWs have one or more “lovers”, many of whom also have multiple FSW partners

• Possibly dense concurrent networks contributing to high HIV prevalence among clients and FSWs in Bagalkot

Additional considerations for transmission dynamics

• Client-FSW partnering patterns:– Client “share” distribution (i.e. client clustering)– Overlapping of client-FSW networks• Higher in brothel and street settings?• Low in home-based and similar settings?

Sex Work System Properties: Client-Sex Worker Mixing Patterns

NetworkClustering

ClientClustering

Ghani and Aral.J Infect Dis 2005.

NetworkIsolation

Even ClientDistribution

Implications for Transmission Dynamics

NetworkClustering

NetworkIsolation

ClientClustering

Even ClientDistribution

Lorenz Curve of the Distribution of Clients Among Female Sex Workers (FSWs) in 8 Cities of

Pakistan

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Cumulative Proportion of FSWs

Cum

ulati

ve P

ropo

rtion

of C

lient

s

Results: Distribution of Client Volume Among FSWs in 8 Cities of Pakistan

City Gini Coefficient

Percentage of Clients Among Top 20% of FSWs

Faisalabad 0.22 32%

Multan 0.22 32%

Peshawar 0.25 35%

Sukkur 0.32 37%

Quetta 0.35 39%

Karachi 0.45 49%

Lahore 0.47 53%

Hyderabad 0.50 56%

Questions to ponder…

• Why doesn’t Sri Lanka have an HIV epidemic among FSWs?– Relatively high per capita FSW population– No circumcision– Programs rudimentary

• What is the likely trajectory of FSW epidemics in different parts of China?

• What is the relative contribution of FSW networks to HIV epidemics in Africa?– East and Sub-Saharan? South? West?

Program Science and Sex Work – What Might be Needed?

• Coherent description of what knowledge is needed for programs:– According to the phase of the program planning and

implementation cycle– Identifying “fixed” (i.e. generalizable) and “variable”

knowledge components• A conceptual framework to guide research questions

that can be applied• Consistency of program-embedded research across

contexts to address key conceptual and knowledge gaps

Sex Work Organization• Locations / venues• Locus of control

• FSW-Client interfaces

FSWs

Macro-Level Societal Context• Socio-cultural milieu

• Demography• Economy• Geography• Political / legal

FSW characteristics• population size• socio-demographics• economic status

Clients

Client characteristics• population size• socio-demographics• economic status

Interactive influences

Aggregate properties• Client volume• Condom use• Duration in SW

Structural patterns• FSW-Client partnering• Network structures• Cohort effects

Transmission dynamics and epidemic trajectory

Thank you