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Mapping of MARPs and
    Strategic Planning
        Dr. Ajith Karawita MBBS, PGDV, MD
National STD/AIDS Control Programme, Sri Lanka
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
Understanding the epidemic
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.
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
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
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
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%
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+
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
HIV prevalence among MSM
HIV PREVELANCE %




                                                    0.5%


                      0.0%

                      2008                           2009
                             Source: NSACP /Sentinel Suveillance Data
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
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
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)
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
Mapping of MARPs in Sri Lanka
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
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
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.
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
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.
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.
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)
Anuradhapura District
Anuradhapura District – FSW spots
Anuradhapura District – FSW spots – Thematic map
Anuradhapura District – MSM spots
Anuradhapura– MSM spots – Thematic map
Colombo District
Colombo District – FSW spots
Colombo District – FSW spots – Thematic map
Colombo District – MSM spots
Colombo District – MSM spots – Thematic map
Batticaloa District
Batticaloa District – FSW spots
Batticaloa District – FSW spots – Thematic map
Batticaloa District – MSM spots
Batticaloa District – MSM spots – Thematic map
Nuwara’Eliya District
Nuwara Eliya District – FSW spots
Nuwara Eliya– FSW spots – Thematic map
Nuwara Eliya District – MSM spots
Nuwara Eliya – MSM spots – Thematic map
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
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
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
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
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.
Acknowledgement to partners of this mapping study




Ministry of Health
    Sri Lanka


                                Community Strength
                              Development Foundation




                                   Sri Lanka Police
Mapping of MARPs, Sri Lanka

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Mapping of MARPs, Sri Lanka

  • 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
  • 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.
  • 20.
  • 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)
  • 27. Anuradhapura District – FSW spots – Thematic map
  • 29. Anuradhapura– MSM spots – Thematic map
  • 31. Colombo District – FSW spots
  • 32. Colombo District – FSW spots – Thematic map
  • 33. Colombo District – MSM spots
  • 34. Colombo District – MSM spots – Thematic map
  • 37. Batticaloa District – FSW spots – Thematic map
  • 39. Batticaloa District – MSM spots – Thematic map
  • 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