6th CEN Conference

Session

Methods in epidemiology 2

20 May 2026, 13:45

Room 13 A

Conveners

Methods in epidemiology 2

• Sharon-Lise Normand (Harvard Medical School)

11. Detection of Measurement Errors and Heterogeneity During the Collection of Observational Data: A Simulation Study

Ronja Foraita (Leibniz Institute for Prevention Research and Epidemiology - BIPS)

20/05/2026, 13:45

oral presentation

In field studies, measurements are often collected over extended periods, during which subtle shifts in data quality or instrument performance can occur. Recognizing and quantifying such measurement heterogeneities over time is essential to ensure the validity of study results and to intervene at an early stage if possible. However, the performance of available statistical approaches for...

127. Detecting Temporal Measurement Heterogeneity in Cohort Studies: Lessons from the Study of Health in Pomerania

Carsten Schmidt (University Medicine Greifswald City: Greifswald)

20/05/2026, 14:03

oral presentation

Longitudinal observational studies and clinical trials routinely collect extensive phenotypic data under changing organisational, technical, and environmental conditions. Variations in examiners, devices, protocols, or ambient factors can introduce consequential forms of measurement heterogeneity and measurement error over time. Although these sources of bias are well recognised, systematic...

211. Navigating Complexities in Assessing Systemic Health Effects of Tattoos in a Population-Based Cohort

Narges Ghoreishi (Department Exposure, Unit of Epidemiology statistics and exposure modelling, German Federal Institute for Risk Assessment (BfR))

20/05/2026, 14:21

oral presentation

Background: Tattoos and permanent make-up (PMU) gain increasing popularity, yet their potential systemic health implications remain poorly understood.
Methods: To investigate associations between tattoos/PMU and chronic disease outcomes, we analyzed data from the LIFE-Adult Study, a population-based cohort of 10,000 adults recruited in Leipzig, Germany (2011–2014). A dedicated...

29. Beyond Case Counts: Simulation Evidence for Probability-Based Pandemic Surveillance

Inken Siems (Trier University)

20/05/2026, 14:39

oral presentation

High-quality data are essential for reliable epidemic surveillance. Traditional systems relying on passive case reporting that may lead to unreliable prevalence estimates depending on the specific disease. Using the example of the COVID-19 pandemic, we show that once prevalence exceeds moderate levels, conventional reporting becomes biased and unstable. Beyond this point, drawing additional...