The document presents a comprehensive mapping of the most at-risk populations (MARPs) and strategic planning for HIV interventions in Sri Lanka. It includes demographic data, HIV prevalence rates among various groups, and details on the geographical distribution of hotspots for interventions. The mapping process utilizes different methodologies to estimate the size and typology of populations, aiming to inform targeted HIV prevention strategies and improve monitoring and evaluation efforts.

1. Mapping of MARPs and
Strategic Planning
Dr. Ajith Karawita MBBS, PGDV, MD
National STD/AIDS Control Programme, Sri Lanka

2. Category Sri Lanka
Land area (sq km) 62,705
Provinces 9
Districts 25
Grama Niladari Divisions
14,013
(GND)
Estimated mid year
population 20 million
(2005)
Population density
313.7
(Person per sq km)
Average annual growth
1.1
rate (1981-2001)
2

3. Understanding the epidemic

4. HIV Epidemic in Sri Lanka
• First AIDS case reported (A Foreigner)
1986
• First Sri Lankan with HIV reported
1987
• First locally acquired HIV infection
1989
Prepared by SIM Unit, National STD/AIDS Control Programme, Sri Lanka, 2010.

5. National Estimates
Category Value
Adult HIV prevalence (15-49) 0.02%
Total PLHIV (2009) 3000
Male: Female Ratio 2:1
Children 35
New infections per year 350
Total ART need 500
One new infection pre day

6. Reported Numbers
HIV cases reported to National STD/AIDS Control Programme
as of 3rd Quarter 2011
Cumulative number of HIV cases 1431
Cumulative number of AIDS deaths 246
Cumulative number of children infected with HIV 52
(MTCT)
Cumulative number of HIV patients on ART (including 207
children)
Cumulative number of infected children on ART 11
Male: Female ratio 1.4: 1
Two new HIV cases are reported per week

7. Number of new HIV cases reported to National STD/AIDS
Control Programme, Sri Lanka as of end December 2010
Total Male Female Linear (Total)
160
137
140 129
119 121
120
102
100 95
91
92
80
Count
68 77
69
55 54 65 63
60 60
47 50 54 55 54
42
37 45 44
40
27 30 32 37 37 40 39
23 22 34
26 29
26 24 28 26 31
20 11 13 24
7 19 20 18 20 19
15 12 16
2 3 8 6 10 8 11 8 10 10
0 2 3 3 1 3
0 0
-20
Year

8. Cumulative HIV cases by mode of
transmission as of end December 2010
Hetero
82.5%
Homo/Bi
11.3%
Perinatal IDU
Blood
4.4% 0.6%
0.3%

9. Distribution of HIV cases by age and year
20
18
2006
16 2007
14 2008
12 2009
2010
10
2 per. Mov. Avg. (2006)
8
2 per. Mov. Avg. (2007)
6 2 per. Mov. Avg. (2008)
4 2 per. Mov. Avg. (2009)
2 2 per. Mov. Avg. (2010)
0
0-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50+

10. HIV prevalence among
female sex workers (FSWs)
2 YEAR MOVING AVERAGE
HIV PREVELANCE %
0.20%
0.16%
0.14% 0.13%
0.07%
0% 0% 0% 0%
2000 2001 2002 2003 2004 2005 2006 2007 2009
Source: NSACP /Sentinel Suveillance Data

11. HIV prevalence among MSM
HIV PREVELANCE %
0.5%
0.0%
2008 2009
Source: NSACP /Sentinel Suveillance Data

12. HIV prevalence among
STD clinic attendees
2 Period Moving Average
HIV PREVELANCE %
0.36%
0.28%
0.2% 0.15%
0.13 %
0.08% 0.09% 0.08% 0.04 %
2000 2001 2002 2003 2004 2005 2006 2007 2009
Source: NSACP /Sentinel Suveillance Data

13. HIV prevalence among TB patients
2 Period Moving Average
HIV PREVELANCE %
0.13 %
0.11% 0.07%
0.06% 0.08%
0.00% 0.00% 0%
0%
2000 2001 2002 2003 2004 2005 2006 2007 2009
Source: NSACP /Sentinel Suveillance Data

14. Epidemic status
• Low prevalent country (HIV prevalence in any
subgroup is less than 5%)
• Truncated type of epidemic in returning
migrant workers
Target Populations for interventions
Most at risk populations (MARPs)

15. High Risk Groups (HRGs)
High risk groups Additional populations
1. Female sex workers (FSWs) 1. Heterosexual men and
2. Men who have sex with women with multiple
men (MSM). sexual partners
3. STD clinic attendees 2. Prisoners
4. Clients of FSWs 3. Populations surrounded by
5. Injecting drug users (IDUs) armed conflict
4. Female domestic workers
5. Street children
Be careful when naming a group according to the occupation
Behaviour is the risk. NOT the occupation

16. Mapping of MARPs in Sri Lanka

17. District profile
Colombo A.pura Batticaloa N’Eliya
North
Western Eastern Central
Anuradhapura Location Central
province Province Province
Province
Batticaloa Area 1.08% 10.6% 3.0% 2.6%
Mid Year
2,400,000 791,000 523,000 742,000
Population
Population 3,581/sq. 118/sq.k 186/sq. 412/sq.k
Density km m km m
Colombo
MOH
18 19 14 13
Nuwara Eliya Areas

18. Mapping Methodology
Pre-
mapping
The pre-mapping:
Level 1 data Preparatory activities –
collation Studying maps, Permission
and authorization, Zone
demarcations, Organization
of research teams, logistics
etc.
Level 2 data
collection
Data Spot validation
analysis Spot list

19. Typologies of MARPs mapped
Female Sex Workers MSM
1. Brothel based 1. Nachchi (effeminate males/TG)
2. Street based
3. House /Shanty based 2. Gays
4. Lodge/Hotel based 3. Male Sex Workers (MSWs)
5. Massage parlor
6. Karaoke bars 4. Beach boys (They are a group
7. Night clubs of males (homo, hetero or
8. Vehicle based - Vehicle based bisexual) cruising in and around
sex workers are those who beach areas, who associate with
operate from closed type of tourists as a guide, animator or
vehicles (cars, vans etc.) in areas provider of any form of
with high demand for sex
workers. Usually these vehicles entertainment including
provide sex workers to clients insertive or receptive sex
and sometimes vehicle space for
sex.

21. Spots identified during L1 and L2 interviews
by districts and MARPs
Number of female sex worker spots
Nuwara
A.pura Colombo Batticaloa Total
Eliya
# of spots in L1 626 1429 244 531 2830
# of active spots (L2) 311 1066 191 370 1938
Number of MSM spots
Nuwara
A.pura Colombo Batticaloa Total
Eliya
# of spots in L1 75 653 118 154 1000
# of active spots (L2) 77 652 95 122 946

22. Mapping can generate
• Number and distribution of hotspots with its typology
• Size estimation of the population concerned according to the
– Geographical zones e.g. City/town, district
– Type of MARPs
– Sub-typologies of MARPs
• Size of population according to the pattern they operate
– On a usual day, on a peak day, what is the peak working
hours etc.
• Type of the spot according to the seeking risk or taking risk.
• Detail information on a profile of MARPs by variables of
interest.

23. Mapping can generate cont.
• Extrapolation and generation of district or national estimates by
the application of different model approaches i.e. Regression
model and percentile approaches.
• GIS maps with hot spots
• Has many more alternatives and adjustments to answer research
questions, or objectives of your project planning and
implementation.

24. National Estimates for Sri Lanka
National estimate for FSWs
41,285 (33,429 - 49,141)
National estimate for MSM
32,796 (25,677-39,915)

25. Anuradhapura District

26. Anuradhapura District – FSW spots

27. Anuradhapura District – FSW spots – Thematic map

28. Anuradhapura District – MSM spots

29. Anuradhapura– MSM spots – Thematic map

30. Colombo District

31. Colombo District – FSW spots

32. Colombo District – FSW spots – Thematic map

33. Colombo District – MSM spots

34. Colombo District – MSM spots – Thematic map

35. Batticaloa District

36. Batticaloa District – FSW spots

37. Batticaloa District – FSW spots – Thematic map

38. Batticaloa District – MSM spots

39. Batticaloa District – MSM spots – Thematic map

40. Nuwara’Eliya District

41. Nuwara Eliya District – FSW spots

42. Nuwara Eliya– FSW spots – Thematic map

43. Nuwara Eliya District – MSM spots

44. Nuwara Eliya – MSM spots – Thematic map

45. Before start interventions
1. Geographical area of interventions
– MOH areas
– VillageGS divisionDS divisionsDistrictsProvincesNational
– Pradesiya sabhaUrban councilMunicipal councilElectorate
2. Population group
– Groups practicing high risk activities (FSW, MSM, STI clinic attendees etc)
3. Size of the target population (Denominator)
– This is the most difficult part – Most of MARPs are hidden and difficult to
reach
– Different size estimation methodologies can be used ( from simple head
counting to Mapping, Multiplier method, Capture-recapture method etc.)
4. Coverage in terms of geography and population
– This is easy once the denominators are established

46. General target for behaviour change
• 80% coverage of population leading to 60%
behaviour change can reverse of the epidemic
60% behaviour Lead to reverse the
80% coverage
change epidemic status

47. Use of mapping data for strategic planning
• Help in the understanding of the magnitude of the MARPs for
interventions.
• Provide information for advocacy and creating enabling
environment for TIs
• Provide information for planning of targeted interventions for
MARPs
• Provide size of population groups and typologies
• Provide denominators for monitoring and evaluation of TIs
• Monitoring of MARPs related indicators and at project
level, national level and international level.
• Help in the strengthening of HIV surveillance in a country

48. Use of mapping data for strategic planning
• Mapping data facilitate sampling of MARPs for surveys and
studies
• Provide information for the generation of HIV estimates by
modeling (EPP, Spectrum)
• Help in setting coverage for prevention interventions
• Resource mobilization
• Project proposal development and financial allocations
• Miro-planning of interventions for MARPs

49. Conclusion
• Number of FSWs and MSM is not easy
to estimate with precision since these
numbers are live and moving.
• However, these estimates are more
practical and useful denominators for
programme planning, monitoring and
evaluation of HIV prevention
interventions for MARPs.

50. Acknowledgement to partners of this mapping study
Ministry of Health
Sri Lanka
Community Strength
Development Foundation
Sri Lanka Police