Improving cohort coverage estimation using a data triangulation framework: the Swiss HIV Cohort Study example.

Abstract

Objectives: To improve estimation of cohort coverage in the Swiss HIV Cohort Study (SHCS) using a data triangulation framework that compares SHCS data with multiple external data sources.

Design: Retrospective longitudinal analysis of the SHCS.

Methods: Cohort coverage of HIV diagnoses, AIDS diagnoses, and antiretroviral therapy (ART) uptake was triangulated across SHCS data (1985-2023), national HIV/AIDS surveillance (1985-2023), longitudinal antiretroviral therapy (ART) sales data (2017-2024), and a targeted literature comparison. Temporal trends in cohort coverage were assessed, and demographic representativeness was evaluated by sex, age, HIV acquisition mode, and region. Mean cohort coverage estimates were calculated for three outcomes: HIV and AIDS diagnoses (Step 1) and ART uptake (Step 2).

Results: Over 38 years, mean SHCS coverage was 62.4% for HIV diagnoses, 74.0% for AIDS, and 64.9% for ART uptake, consistent with literature-based estimates. Coverage of HIV diagnoses declined in recent years, and geographical heterogeneity was observed. The SHCS remained broadly representative across most subgroups; however, females, older adults, and people with heterosexually acquired HIV or using psychoactive substances were underrepresented, while people on single-tablet and salvage ART regimens were overrepresented.

Conclusions: A data triangulation framework provides a practical approach for monitoring cohort coverage and representativeness. While the SHCS captures a broadly representative sample of diagnosed individuals, tailored strategies are needed to improve inclusion of underrepresented subgroups and maintain cohort coverage. Sustained monitoring is essential to ensure that cohort-based research remains generalizable and continues to inform clinical care and public health responses in Switzerland and beyond.