This year there will be six interactive pre-conference workshops in morning and afternoon sessions that take place on Wednesday June 21st, 2023. Five will be held at the Erasmus Medical Center in Rotterdam, one will be held online. Please note that the live pre-conference workshops have limited availability, so please make sure to register in time. The online pre-conference workshop is free and open for anyone. Please find more details below.
Summary of pre-conference workshops
| 09.00 – 13.00 | What to do when you have unmeasured confounding (which is always) by dr. Jeremy Labrecque (LIVE) |
| 09.00 – 13.00 | Embracing uncertainty using decision modeling by prof. dr. Myriam Hunink & Stijntje Dijk (LIVE) |
| 09.30 – 12.00 | Big data, AI and Machine learning for epidemiologists: how to teach! by spear group Education (VvE) (ONLINE) |
| 14.00 – 17.00 | Communication in health policy and research focusing on minorities, migrants, and groups of challenged literacy by Heleen Koudijs & Rania Albeno-Jabrah (LIVE) |
| 14.00 – 17.00 | Structured expert judgment: addressing biases and reproducibility of eliciting knowledge in times of uncertainty by prof. dr. Mark Burgman & dr. Tina Nane (LIVE) |
| 14.15 – 17.15 | ‘Making sense out of incomplete data’ by Special Interest Group for Applied Infectious Disease Epidemiology (VvE) (LIVE) |
Live pre-conference workshops – details:
Location: Erasmus MC, Rotterdam
Date: Wednesday 21 June, 2023
Time: morning (9:00-13:00) and afternoon (14:00-17:00)
Registration open: 27 March 2023
Registration fee: 25 euros
Organisers: Jeremy Labrecque (chair), Roos Hijdra, Luc Coffeng
Maximum number of participants per workshop: 25 people
Language: English
Please note that no lunch is provided.
1. What to do when you have unmeasured confounding (which is always)
Time: 9:00-13:00
Speaker: dr. Jeremy Labrecque
Workshop description
Most epidemiologic papers have a sentence in the discussion stating that, “the possibility that the results are due to unmeasured confounding cannot be eliminated.” Given how quantitative epidemiology is, it is strange that so many of us are satisfied with such a vague, qualitative statement. This workshop will teach and apply (using R) how use different bias analysis techniques–including E-values, probabilistic bias analysis and partial identification–to better deal with the possibility of unmeasured confounding. This workshop will be aimed at applied researchers and requires no background in causal inference.
2. Communication in health policy and research focusing on minorities, migrants, and groups of challenged literacy
Time: 14:00-17:00
Speakers: Heleen Koudijs & Rania Albeno-Jabrah from PHAROS.
Workshop description
How do you make health promotion efficient? How do you ensure that your research is inclusive and accurately represents a studied population? What does culturally sensitive communication mean for daily research and policy practice? In this workshop participants will focus on inclusive research, cultural sensitivity in research and policy making and effective communication with people with lower health literacy. We look at topics such as overcoming language barriers, cultural bias, informed consent and information materials. Although the workshop will include some theoretical backgrounds, the main focus will be on group interaction, sharing of relevant experiences and practical exercises.
3. Structured expert judgment: addressing biases and reproducibility of eliciting knowledge in times of uncertainty
Time: 14.00-17.00
Speakers: prof. dr. Mark Burgman & dr. Tina Nane
Workshop description
Informing decisions in times of uncertainty is challenging, for instance policy or clinical decisions related to the management of COVID-19. Expert knowledge or judgement is important in these situations, but eliciting it can be fraught with problems and biases. This workshop will provide an introduction to and hands-on experience with structured expert judgement (SEJ). SEJ encompasses a suite of methods and tools to elicit expert judgement in a reproducible fashion, minimising potential biases that might occur. The workshop will include several exercises to elicit judgements to show how unstructured procedures can fail and how this can be improved on with SEJ. We will close with a discussion of how individual experts’ judgement can be differently weighted based on their estimated expertise, i.e., based on how well they perform in a set of problem-specific test questions.
4. Embracing uncertainty using decision modeling
Time: 9:00-13:00
Speakers: prof. dr. Myriam Hunink & Stijntje Dijk
Workshop description
Decision modelling encompasses a set of quantitative tools used to integrate evidence and values in order to inform clinical and public health decision makers. The tools are specifically developed to make decisions in the face of uncertainty. In this workshop we will introduce you to decision trees, state-transition cohort models, and microsimulation models. We will discuss how heterogeneity can be modelled. Subsequently we will explain how we evaluate the effect of uncertainty in the parameter inputs of these models using sensitivity analysis and probabilistic analysis. Finally, we will introduce you to value of information analysis which is a method that calculates whether further research is necessary and justified given the current evidence and its uncertainty.
5. Making sense out of incomplete data
Time: 14.15-17.15
Speakers: Dr. Sonia Boender & Dr. Alma Tostmann, on behalf of the Special Interest Group ‘Applied Infectious Disease Epidemiology’
Workshop description
When responding to an infectious disease outbreak or other crisis situation, your data will be messy, answers are needed – FAST – and society will have already started to draw its own conclusions… How can epidemiologists draw reliable conclusions and communicate clear recommendations based on science at times of uncertainty?
In this preconference workshop, the Special Interest Group “Applied Infectious Disease Epidemiology” embraces uncertainty that comes with the profession of so-called “field epidemiology”. Experts working in surveillance, humanitarian assistance, hospital epidemiology and risk communication will share their experience and tricks of the trait when applying field epidemiology in a dynamic setting. We conclude with a hands-on case study of a real-life infectious disease outbreak.
Online pre-conference workshop – details:
1. Big data, AI and Machine learning for epidemiologists: how to teach!
Time: 9.30-12.00
Speakers: dr. ir. Peter van Ooijen; Prof. dr. Carl Moons; dr Lilian Peters
Workshop description
Big data, AI and machine learning has become a hot topic in many areas of education and research. They can be used to address novel questions in epidemiology. There is a current trend to integrate them in the curricula as skills needed to prepare students and researchers for the future. With this workshop we want to address questions such as: “How can we integrate AI/BIG data in epidemiology education? What should an epidemiologist learn and be able to do in this are? What level of skills must be attained? During this workshop we will listen to expert’s presentations and discuss how these questions can be answered.