Course description
This doctoral-level course equips students with both the theoretical foundation and applied skills to measure population-level burden of disease and its economic impact, with a particular focus on low- and middle-income countries. Through a combination of lectures and hands-on workshops, students will critically assess current methodologies, explore the limitations and advantages of various approaches, and learn how to work with publicly available secondary datasets to develop original research questions. The course emphasizes practical experience in estimating mortality, morbidity, and economic burden using real-world data and fosters critical thinking about the ethical and methodological challenges in global health metrics and economics.
Topics covered include:
- Estimating mortality, life expectancy, years of life lost (YLL), morbidity, and years lived with disability (YLD) in settings lacking complete vital registration systems
- Disability weights: methods and tradeoffs between mortality and morbidity
- Theoretical approaches to valuing changes in health outcomes
- Estimating economic burden through cost-of-illness and value-per-statistical-life frameworks
- Overview of key secondary data sources in global health (e.g., Global Health Estimates, Global Burden of Disease, Demographic and Health Surveys)
- Best practices for conducting original research using secondary health data
By the end of the course, students will:
- Demonstrate intermediate-level understanding of key theories and methods used to estimate disease and economic burden in global health
- Gain practical experience in leveraging secondary datasets to conduct original analyses
- Understand ethical considerations and methodological challenges in global health metrics and economics
Content: 4 consecutive full-days. We will spend about 60% of the time on lectures, and the remaining on hands-on workshops and discussions.
Participants: Participants in this course should have some prior experience with, ideally R, or Python and STATA. Novice users should consider the course “Introduction to R”. Students should bring their own laptop. PhD students from all disciplines at Danish and international universities with an interest in global health metrics and economics. Ideally with master’s training in one of the relevant quantitative fields, such as epidemiology, economics, demography, and public health.
Lecturers
- Angela Y. Chang, Associate Professor, Danish Centre for Health Economics, SDU
- Julia Callaway, Assistant Professor, Interdisciplinary Centre on Population Dynamics (CPop), SDU
- Rasmus Skov Olesen, Postdoctoral fellow, Danish Centre for Health Economics, SDU
- With guest lectures from the World Health Organization, Institute for Health Metrics and Evaluation, Harvard School of Public Health.
Course Fee
The course is free of charge for PhD students enrolled in Universities that have joined the "Open market agreement" or NorDoc.
For other participants there is a course fee of
DKK 2900
EUR 389