The document discusses Sri Lanka's methodology for estimating HIV prevalence and projections using the Spectrum software. Key data sources for the model include surveillance data, program statistics on PMTCT, ART, and child treatment. Subpopulations like FSW, MSM, and drug users are modeled separately. Calibration is done to fit curves to available data. Estimated numbers of people living with HIV, new infections, and deaths in Sri Lanka are higher than reported numbers, suggesting the need for improved data and assumptions. The Spectrum software methodology produces national HIV estimates but has limitations for low prevalence settings like Sri Lanka.

1. HIV estimations and projections;
an overview of the methodology used in
2015
Dr K.A.M. Ariyaratne
Consultant Venereologist | Coordinator Strategic Information
National STD/AIDS Control Programme, Sri Lanka

2. Objective of this Presentation
• An Overview of the Current HIV estimation
method
• What data and assumptions used for Sri Lanka
during 2015

3. Estimated number of adults and children newly infected with HIV  2013
Middle East & North Africa
25 000
[14 000 – 41 000]
Sub-Saharan Africa
1.5 million
[1.3 million – 1.6 million]
Eastern Europe
& Central Asia
110 000
[86 000 – 130 000]
Latin America
94 000
[71 000 – 170 000]
Caribbean
12 000
[9400 – 14 000]
Total: 2.1 million [1.9 million – 2.4 million]
Asia and the Pacific
350 000
[250 000 – 510 000]
North America and Western and Central Europe
88 000
[44 000 – 160 000]
In 2013 there were 2.1 million new HIV infections

4. Why do we need HIV estimations?
• To provide HIV programme managers with estimated
numbers relevant to HIV epidemic
• To use in strategic planning for prevention and care
services
• For advocacy purposes: numbers infected, numbers dying
• For impact assessment e.g. Expansion of ART programme
• For global reporting/Comparing country Scenarios

5. Loss of patients in the AIDS
treatment cascade

6. 10th of July
2015
Software used for HIV estimations

7. About the Spectrum Software
• Software developed by Avenir Health (Futures Institute)
and East-West Center. Updated routinely
• Guidance from UNAIDS Reference Group on Estimates
Modelling and Projections www.epidem.org
• Meetings to consider issues and refine
• Engage with research institutes and individuals to answer
specific questions
• Methods published in peer-reviewed journals every
other year

8. Full model for R-Spline and R-Trend is same except for r(t) calculation
8Source: East West Center and Futures Institute 2013

9. Need Quality Data and Good
Assumptions
garbage in, garbage out

10. Outline of the Estimation Process
Demographic Data
Program Statistics
Epidemic Patterns
Surveillance and
Survey Data
Demographic and Epidemic
Calculations
• Mother-to-child transmission
• Child model
•Adult model
Prevalence /
incidence trend
Results
• Number HIV+
•New Infections
•AIDS deaths
•Need for ART
•Need for PMTCT

11. Step 1. Creating a projection

12. Step 2. ART elibgibility Criteria

13. Step 3. HIV Programme Statistics
• Programme Statistics
1. PMTCT data
2. ART data
3. Child treatment data

14. Cont., HIV Programme Statistics

15. Step 4. Calculating Incidence
EPP (Estimation and
Projection Package) with
Adult (15-49) used.

16. 4.1 Incidence: Configuration
1. Define the epidemic structure.
1. Concentrated /Low level epidemic
2. Define the sub-population characteristics
1. Estimated population size
2. Whether people are likely to move in and out of this
sub-population
3. Enter the estimated time (in years) that a person
spends in that sub-population.
HIV sentinel survey and
IBBS data used.

17. 4.2 Sub-populations
1. FSW
2. MSM
3. Drug users
4. Client of FSW
5. Male Remaining
6. Female Remaining

18. 4.3 Entering surveillance data
HIV sentinel survey and
IBBS data used.

19. 4.4 Sub-population sizes

20. 4.5 Sub-population - Turn overs

21. 4.6 Sub-population - Turn overs
• Following subpopulations were included
1. Drug Users (time in DU 10 years → male
remaining pop.)
2. MSM (No turn over)
3. Sex worker clients (time in group 7.5 yrs →
male rem. Pop)
4. Sex workers (Time in group 5 yrs → female
remain pop)
5. Male remaining population (NA)
6. Female remaining population (NA)

22. 4.7 Incidence: Curve fitting
• Spectrum 2015 offers four fitting methods
• R-Spline
• R-Trend
• EPP Classic
• Workbook
• One-click fitting
• Fit all
• Allows multiple projections to be fit

23. 4.8 Models available in EPP 2015
• R-Spline (default)
• Applies a set of smooth mathematical functions to give
smoother incidence curves
• R-Trend
• Draws on past experience with trends in r observed in
actual epidemics to produce a smooth curve
• EPP Classic
• A four parameter model that is useful in low data
situations and produces an epidemic that rises and
plateaus

24. Curve generated for MSM

25. Calibrating the curves
• FSW no calibration done
• Clients of sex workers FSW rate down calibrated
by 0.5
• MSM up calibrated by a factor of 1.2
• DU no calibrations
• Male remaining pop- Urban ANC prevalence used
with a down calibration by a factor of 0.5
• Female remaining pop -Urban ANC prevalence
used with a down calibration by a factor of 0.5

26. Shapes of final curves fitted

27. Getting Results with
Spectrum

29. Reported Vs. Estimated numbers
Reported Numbers - 2014
• Number living with HIV 1737
(Reported – Deaths) (53% of est.)
• New infections in 2014 228
• Deaths in 2014 26
• Adult HIV prevalence 0.03%
Estimated numbers - 2014
• Number living with HIV 3300
• New infections in 2014 <500
• Deaths in 2014 <200
• Adult HIV prevalence <0.1%
KAM Ariyaratne/ National STD/AIDS Control Programme/21.09.2015

30. Outputs1. HIV pop by risk groups

31. Outputs: 2. New HIV infections.
Too many DU new infections than actual data

32. Summary
• Spectrum software used in the recent HIV estimation
• Software is getting improved over the time and
subjected to very frequent software updates
• Methodology is less sensitive to very low prevalent
epidemic
• Better programmatic data, surveillance data and beter
assumptions will produce reasonable estimates