Research Unit

Global Burden of Disease &
Estimation Unit

Quantifying disease burden, risk factors, and health outcomes through advanced epidemiological modelling, data science, and global health metrics.

GBD Analytics DALYs · YLLs · YLDs Comparative Risk Assessment Forecasting

The GBD Estimation Unit aims to : 1) Organize and Intergrate local data in GBD Estimations ,2)Strengthen local network in GBD research and collaboration , and 3)Promote translation of GBD research evidence into Resource Allocation and Burden Tackling.

Team members are specialized in the quantification and analysis of population health using standardized global metrics.

By integrating epidemiological methods, statistical modelling, and large-scale health datasets, the unit generates robust estimates of disease burden, mortality, morbidity, and risk factor attribution across different populations and time periods.

Building on expertise in local and global collaborations in GBD estimations , the GBD unit will apply methods aligned with the Global Burden of Disease framework, including disability-adjusted life years (DALYs), years of life lost (YLLs), and years lived with disability (YLDs). These approaches support evidence-based decision-making, priority setting, and strategic health planning at national and international levels.

Core Capabilities

  • Global Burden of Disease estimation (DALYs, YLLs, YLDs)
  • Comparative risk assessment and attributable burden analysis
  • Advanced statistical modelling and uncertainty quantification
  • Integration of AI and machine learning for health data analysis
  • Time-series analysis and forecasting of disease burden
  • Health metrics evaluation and cross-country comparisons
  • Data harmonization and large-scale epidemiological database management

Research Areas

  • Burden and epidemiology of infectious diseases in low- and middle-income countries, including tuberculosis (TB), malaria, and HIV/AIDS
  • Impact of pandemics and emerging infectious diseases on mortality, morbidity, and health system performance
  • Risk factor attribution and disease drivers, including antimicrobial resistance (AMR) and other determinants of health outcomes
  • Forecasting and modelling future disease burden under different intervention strategies and policy scenarios