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

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

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

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 www.iedea.org

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 2009-2014.

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.

Field tracing of patients lost to follow-up

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

Mortality in patients lost Zurcher et al submitted

Undocumented transfer Zurcher et al submitted

Treatment interruption Zurcher et al submitted

Correcting mortality for loss to follow-up Egger M et al. PLoS Med. 2011;8:e1000390

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 1.64397 1.814623 2.03894 6-12 2.189916 1.697969 1.740988 50-99 >12 1.975792 2.696108 1.414255 2.048315 1.622381 1.40328 100-199 2.072795 2.102754 1.556734 2.040634 1.702032 1.701063 200-249 1.964165 2.634279 1.680239 1.91695 1.612833 1.333495 250-349 1.967266 1.616284 1.311076 1.993837 1.61538 1.442466 350-499 2.695073 1.959174 3.695248 2.353412 2.213003 1.302914 >=500 2.800414 1.579218 3.79234 1.96031 2.299502 1.969346 Etc. Anderegg et al submitted

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

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

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

Reserve slides

Study-level determinants of mortality Variable Crude   Adjusted* OR (95% CI) aOR (95% CI) Calendar year Per 1-year increase 0.84 (0.74-0.96) 0.86 (0.78-0.95) Study duration 0.82 (0.74-0.92) 0.84 (0.77-0.92) Setting Rural 1 Urban 0.51 (0.25-1.01) 0.59 (0.36-0.98) Population Children Adults 1.51 (0.63-3.62) 1.47 (0.78-2.78) *adjusted for all variables listed

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

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):333-342. 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.

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Comparisons between methods