My research

Trained as an Epidemiologist, my research is focused on causal inference, complexity and life course mechanisms in health research. Health is a complex phenomenon, and I am studying the social and biological factors determining health and disease in populations. I am leading the DANLIFE project, in which we leverage multi-dimensional exposome data covering the totality of measured lifetime exposures across multiple social, environmental and biological dimensions to study the health consequences of social and environmental adversities. I have a particular interest in causal inference theory and how it intersects with methodological insights from complex systems theory. To embrace complexity in epidemiology I actively explore new sources (e.g. smartphones) of ‘big data’, incorporate system theory and leverage insights across disciplines. I am also involved in several citizen science projects with a direct societal engagement and impact.

I am Chair of the Section of Epidemiology at University of Copenhagen, where I am also leading the interdisciplinary Complexity and Big Data Group.

Fellowship

The application of complexity theory to public health is an emerging field, and debates about how to best conceptualize and model complex phenomena in public health remains. Introducing the language and conceptual toolkit of complexity theory to public health involves rejecting, restricting, or modifying fundamental tenets of the formal causal inference approach, including directionality and acyclicity, and thereby reorienting our understanding of disease causation. During my visit to IAS, I aim to explore the landscape of methods and approaches to complexity modelling in public health and relate it to the causal inference framework of modern epidemiology.