ESHS/HSS Annual Meeting

Epidemiology Unbound 2

Session Submission Type: Organized Session

English Abstract

This symposium will explore the impact of epidemiology on the sciences across the twentieth century. While much of the modern history of epidemiology has considered the field’s uncertain status as a ‘secondary science’, or followed the rather technical development of its methods and theories, this symposium will ask for the traces of a distinct epidemiological kind of reasoning beyond the field of epidemiology.

To do this, papers in this symposium engage with epidemiological reasoning as a 'style of thinking' concerned with the dynamics of health and disease in communities, crowds, societies, and populations; a perspective with considerable distance to clinical perspectives on health and disease.

The papers in this symposium will critically assess the following questions in three panels:

- What are common principles, characteristics and aspects of epidemiological reasoning in its adaptation, utilisation and integration in fields not originally concerned with subjects of epidemiological concern?

- How has epidemiological reasoning transformed and disrupted disciplinary traditions and conventions and what kind of problems were supposed to be resolved with such transformations?

This second panel (Epidemiology Unbound 2) follows the impact of epidemiological principles in the world of big data and artificial intelligence, reconstructing how epidemiology came to be identified with the data sciences, and to trace the transmission of ideas of bias, network and record linkage beyond the epidemiological domain. The first panel considers the fate of statistical methods and the third panel maps the intersections between epidemiology and the sciences and politics of information.

Sub Unit

• Organized Session

Chair

• Carolina Mayes, University of Edinburgh

Individual Presentations

• Global agendas, local practices: transit of knowledge and epidemiological training in Brazil (1980s - 2000s) - Luiz Alves Araújo Neto, Fiocruz Brazil

• Toward Evidence-Based Artificial Intelligence in Medicine: Lessons from Epidemiology and EBM - Nicolas Brault, UniLaSalle Polytechnic Institute

• From Risk to Relational Complexity: Network-Based Prevention in Latin America - Theo Di Castri, University of Cambridge

• Probabilistic Record Linkage: From Radiation Epidemiology to Big Data - Aaron Sidney Wright, Dalhousie University

Session Organizer

• Lukas Engelmann, University of Edinburgh