1. Knowing your epidemic and knowing your response – maximising routinely collected data to measure and monitor HIV epidemics in sub-Saharan Africa Monitoring mortality in ART programmes
Matthias Egger Institute of Social & Preventive Medicine (ISPM) University of Bern, Switzerland

2. Improvements in life expectancy across the globe
Wandeler et al. Curr Op HIV/AIDS 2016

3. Life expectancy on ART compared to the general population
Poster TUPEB031,
Abstract 4072

4. International consortium established to address clinical and health services research questions
>500 sites in 7 regions, harmonized data collection
> 1 million adults and children
Funded by NIH

5. Retention on ART
Data from 105 cohorts in 41 countries from six IeDEA regions (Southern Africa, Central Africa, West Africa, Asia-Pacific, Caribbean & Central/South America, North America).
301,756 adults and children with HIV who enrolled in an HIV care program and started ART between

6. Linkage with vital registry
Of deaths recorded in patients files after 2003, 94.0% were recorded by civil registration, with higher completeness in urban areas, older adults and females.
Of deaths recorded by civil registration only 35.0% were recorded in patient files
When the information from the two systems was combined, an estimated 96.2% of all deaths were recorded.

7. Field tracing of patients lost to follow-up

8. meta-regression analysis
Meta-analysis and
of tracing studies
Zurcher et al submitted

9. Mortality in patients lost
Zurcher et al submitted

10. Undocumented transfer
Zurcher et al submitted

11. Treatment interruption
Zurcher et al submitted

12. Correcting mortality for loss to follow-up
Egger M et al. PLoS Med. 2011;8:e

13. Correction factors (c)
168 correction factors (2 genders x 3 time periods x 4 age groups x 7 CD4 groups)
2 correction factors
Gender
Age (years)
CD4 count (cells/µL)
ART period
(months)
Correction factors (No. of factors in set)
South Africa (2)
South Africa (168)
Kenya
(168)
Female
15-24
<50
0-6
6-12
50-99
>12
>=500
Etc.
Anderegg et al submitted

14. Sensitivity analyses based on worst and best case scenarios
Anderegg et al submitted
Sensitivity analyses based on worst and best case scenarios

16. Conclusions
Monitoring of mortality in ART programmes requires data on mortality in patients lost to follow-up and patients transferred out
ART programmes should trace patients lost to follow-up to ascertain their status and bring them back to care
National programmes should introduce unique IDs so that patients can be traced across facilities
MESH will develop refine approaches to correcting mortality and develop applications for use in the field

17. Thank you
Special thanks to Nina Anderegg, Leigh Johnson, Beth Zaniewski, Olivia Keiser and our funders

18. Reserve slides

19. Study-level determinants of mortality
Variable
Crude
Adjusted*
OR (95% CI)
aOR (95% CI)
Calendar year
Per 1-year increase
0.84 ( )
0.86 ( )
Study duration
0.82 ( )
0.84 ( )
Setting
Rural 1
Urban
0.51 ( )
0.59 ( )
Population
Children
Adults
1.51 ( )
1.47 ( )
*adjusted for all variables listed

20. South African correction factors East African correction
Sensitivity analyses
South African correction factors
East African correction
Set of two
Set of 168
factors (168)
Southern Africa
6/168 (3.6%)
7/168 (4.2%)
10/168 (6.0%)
Central Africa
4/168 (2.4%)
5/168 (3.0%)
Latin America
Asia Pacific
1/168 (0.6%)
2/168 (1.1%)
East Africa
0/168 (0%)
0/186 (0%)
West Africa
North America
Anderegg et al. submitted

21. Methods for Correction of Mortality Estimates for Loss to Follow-Up after ART Initiation
Double-sampling
Frangakis CE, Rubin DB. Addressing an idiosyncrasy in estimating survival curves using double sampling in the presence of self-selected right censoring. Biometrics 2001;57(2):
Geng EH et al. Sampling-based approach to determining outcomes of patients lost to follow-up in antiretroviral therapy scale-up programs in Africa. JAMA 300; 2008: 506–507.
Multiple imputation
Brinkhof MW et al. Adjusting mortality for loss to follow-up: analysis of five ART programmes in sub-Saharan Africa. PLoS One 2010, 5(11), e14149.

22. Web calculator

23. Comparisons between methods