Pre-conference course

Pre-conference workshops/course

Before the NordicEpi 2024 kicks off, you have the opportunity to participate in one of the exciting pre-conference workshops/courses “How to use the Danish National Birth Cohort for life-course epidemiology research”, “How to use disease burden methods on Nordic registry data”, “Introduction to Complex Systems Methods in Epidemiology and Public Health” or “How to Emulate a Target Trial to Study the Effects of Treatments”. The content of three workshops/courses is described below.

The four workshops run in parallel during the morning of June 12th 2024 (anticipated time 9-12 am). You can register for one of these workshops/courses when you register for the conference.

How to use the Danish National Birth Cohort for life-course epidemiology research

Instructors: Anne-Marie Nybo Andersen, University of Copenhagen

The Danish National Birth Cohort (DNBC) is a unique data source for life-course epidemiology research. Established in 1995 and still counting 180.000 participants, the DNBC is now a rich resource with prospectively collected, longitudinal data allowing for investigation into the causal link between early life exposures and disease in later life - and thus the possibilities for disease prevention. At this symposium we will present the DNBC data available, show you how to gain access to data and unveil some of the many unexplored research opportunities. Current DNBC researchers will present some of their research projects covering various health aspects such as cardiovascular health, cancer, mental illnesses, fertility, etc. Take this opportunity to meet, discuss and find out how DNBC data can be of use in your research. Detailed program can be downloaded HERE

Please note that registration for “How to use the Danish National Birth Cohort for life-course epidemiology research” is separate and via email: to: This email address is being protected from spambots. You need JavaScript enabled to view it. Registration deadline: 7th June 2024. There is no registration fee.

How to use disease burden methods on Nordic registry data

Instructors: Ann Kristin Knudsen, Carl Baravelli and Ingeborg Forthun, Norwegian Institute of Public Health

Disease burden analyses make it possible to compare the impact of different diseases on population health across locations, age, sex, and over time. The core measurement of disease burden is the disability-adjusted life-year (DALY), a summary measure of the health loss of a disease caused by premature mortality and disability. The rich data infrastructure in the Nordic countries provides unique opportunities to extend disease burden analyses beyond age-sex-location characteristics, in addition to increasing the knowledge of disease burden impact beyond mere health loss. In this course, we will a) give an introduction to the rationale behind disease burden analyses and an overview of important concepts and methods, and b) describe and give examples of how disease burden methodology can be used on Nordic administrative registry data.

Introduction to Complex Systems Methods in Epidemiology and Public Health

Instructors: Jeroen Floris Uleman and Naja Hulvej Rod, University of Copenhagen

Many public health problems show features of complex systems characterized by complex interactions and feedback mechanisms among various factors and individuals across different spatial scales. Prominent examples of such complex public health problems include health inequality, obesity, Alzheimer’s disease, multi-morbidity, and infectious disease epidemics. To comprehend and address such complexities, complex systems thinking is an emerging paradigm in public health research.
In this preconference workshop, the participants will be familiarized with methods for complex systems thinking, including causal loop diagrams, designed to capture the dynamic mechanisms that drive public health issues. They will also gain exposure to simulation modelling using system dynamics, enabling them to explore the complexity of these problems and simulate potential interventions. We will illustrate the use of these methods with several case examples.
This workshop has a limited number of seats.

How to Emulate a Target Trial to Study the Effects of Treatments

Instructor: Sonia Hernandez-Diaz, Harvard University

When questions on the comparative effectiveness or safety of treatments cannot be answered using a randomized experiment, decision must be informed by observational data. Causal inference from observational data can be conceptualized as an attempt to emulate a hypothetical pragmatic randomized trial: the target trial. This framework makes each aspect of the target trial protocol explicit, which helps us adhere to basic principles and avoid common methodologic pitfalls such as immortal person time or prevalent user bias. The learning objectives of this course are the following: a) Design the key protocol elements for a target trial and its corresponding observational emulation including specification of the causal question, eligibility criteria, treatment strategies, assessment of outcomes and analytic approach. b) Recognize common challenges for emulating these protocol elements including confounding. We will begin with an overview of basic principles of target trial emulation to then present applications to different causal questions that emphasize specific protocol components, challenges, and solutions.