Format: Lectures, group work, and exercises.
Prerequisites: Basic training in epidemiology and biostatistics is assumed.
Equipment: Laptop. All participants will get a short-course STATA license, which needs to be installed on the laptop.
Morning (9.00 am - 12.00 noon)
This class aims to teach the principles of thinking about ‘finding and refining a research question’. After a lecture on the principles, participants will have the opportunity to try out crafting a research question in an exercise based on data from an investigation that happened in real life. It is assumed that participants know general principles of epidemiology and understand general ideas about disease causes. There is no programming or calculation involved.
Instructor
Jan Vandenbroucke, MD, PhD
Leiden University Medical Center, Aarhus University, and London School of Hygiene and Tropical Medicine
Afternoon (1.00 pm - 4.00 pm)
This class covers an introduction to infectious disease epidemiology, and to the use of the case-control study design specifically applied to infectious diseases. The aim is to understand what is specific to infectious disease epidemiology. After the introductory lecture, participants will make an exercise in study design on risk factors for infections with antibiotic-resistant bacteria.
Instructor
Christina Vandenbroucke-Grauls, MD, PhD
Amsterdam University Medical Centers and Aarhus University
Morning (9.00 am - 12.00 noon)
Causal interpretation of associations is warranted once alternative explanations are credibly ruled out. Information bias stemming from measurement error is one such alternative explanation. Epidemiologic studies based on routinely-collected data have the benefit of hypotheses-free data accumulation, the flip side of which is unknown amount of measurement error. Using lectures and practical group work (Word/Excel), this workshop will cover basics of validity measures, gold standard, conducting validation studies, prioritizing and transportability of event-finding algorithms, and implications for interpretation.
Instructor
Vera Ehrenstein, MPH, DSc
Aarhus University
Afternoon (1.00 pm - 4.00 pm)
In this class, you will first learn how interaction is thought about from a statistical and epidemiological point of view, and how these views differ. Next you will make a hands-on exercise on calculating interactions, based on a real life paper about a gene-drug interaction (a simple calculator suffices, e.g., on your phone with a button for logarithms). Thereafter, current thinking about interaction, according to component cause theory and counterfactual theory, will be explained - based on the same example.
Instructor
Jan Vandenbroucke, MD, PhD
Leiden University Medical Center, Aarhus University, and London School of Hygiene and Tropical Medicine
All day (9.00 am - 4.00 pm)
After a discussion of missing data mechanisms, the course will review ad-hoc methods of dealing with missing data and focus on theory, practice, and reporting of studies using multiple imputation. Computer exercises will be based on Stata.
Instructor
Irene Petersen, PhD
University College London and Aarhus University
All day (9.00 am - 4.00 pm)
Amongst many ways to account for confounding in observational studies, self-controlled methods have been gaining popularity over recent years. Designs such as the self-controlled case series and the case cross-over make comparisons within individuals, and remove the need to account for between person differences.
This course is designed to introduce the self-controlled case series and case cross-over designs to participants. We will explore both methods, their underlying assumptions, some examples of their application, and more recent methodological developments.
Participants will have an opportunity to gain practical experience in conducting analyses for both study designs and will gain experience in thinking through self-controlled design features in small group discussions. The analytical part of the course will involve the use of Stata and will form ~ a quarter of the course.
A small amount of pre-course reading material will be circulated to participants, and it is assumed that participants are already familiar with basic epidemiological study design (e.g. cohort and case control designs) and the statistics underpinning them.
Instructor
Ian Douglas, MSc, PhD
London School of Hygiene and Tropical Medicine
Morning (9.00 am - 12.00 noon)
This final session will solidify the previous material on study designs by showcasing real-world projects applying different study designs to study adverse events following HPV vaccination and COVID-19 vaccination, respectively. Traditional cohort designs, self-controlled designs, and time trend studies will be discussed, together with the possibility of doing rapid “emergency epidemiology” studies based on near-real-time medical databases.
Instructor
Reimar W. Thomsen, MD, PhD
Aarhus University