Project website coming soon
The project, led by Dr Lukas Engelmann, is concerned with the history of epidemiological reasoning in the 20th century. Epidemiology has radically transformed and reshaped approaches to understanding health and disease in science and society since the early 1900s. But this history is often told too narrowly, or in overly broad brushstrokes.
Epidemiology has historically been a niche field in the medical sciences, side-lined by laboratory scientists and clinicians as just a secondary science. However, over the twentieth century, the field and its expertise gained unprecedented authority and influence. Long before Covid-19, epidemiologists had won the trust of policy makers and the general public to define public health crises brought about by infectious diseases, but also for chronic conditions and ‘unhealthy’ lifestyles.
This history expands far beyond the record of a discipline. The project seeks to map the multiple influences - the web of causes - from which Epidemiology emerged as a field in the early twentieth century. And the project follows the dispersion and spread of epidemiological thought into other fields, domains and disciplines over the course of the century.
What is, or what has been called, epidemiology is not the project’s defining focus. This is instead a history of epidemiological reasoning. As a specific way of thinking through phenomena, this project understands epidemiological reasoning as a discrete set of skills that employ data practices, rely on transdisciplinary expertise and utilise theoretical models to infer the characteristics, dynamics and causes of epidemic phenomena. The project’s research is therefore focused on three themes: models, correlation and configuration.
The theme will analyse how stochastic epidemiological modelling endowed epidemiology with scientific status, and how mathematical methods won the discipline unprecedented authority. Case studies in the theme will historically reconstruct the conditions in which epidemiological theories and models were developed, and trace the emergence of epidemic standard models.
The theme will excavate the long history of data practices in epidemiology to understand correlative methods and the field’s unique ethos of induction. Correlating medical data with a plethora of information – vocation, location, religious practices, for example - to facilitate causal inferences has been an essential characteristic of epidemiological reasoning. To uncover the practices and material conditions for correlation, the theme will focus on the discipline’s paper technologies, including reports, forms, schemes and survey structures used for the collection, standardisation and creation of epidemiological data in the early twentieth century.
The third theme will focus on the transdisciplinary history of epidemiological reasoning and the bidirectional influences of vital statistics, demography, sociology, anthropology and ecology on epidemiology as a discipline. The theme will analyse the development of post-war social epidemiology and the disciplinary implications of expanding the epidemic frame from infectious diseases to chronic conditions.