A History of Epidemiological Reasoning

Project Description

The project 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 first to map the multiple influences – the web of causes – from which Epidemiology emerged as a field in the early twentieth century. Second, 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. 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.

Looking at a way of knowing, at how arguments were built and how epidemiological knowledge circulates within and beyond disciplines, empires and thought collectives, will enable the project to broaden the scope of this history. The project gathers a range of impulses from medical statistics, colonial and local administration, anthropology, eugenics and sanitary science (…) that laid the groundwork for epidemiology to become a modern medical science. To understand how epidemiological reasoning assumed scientific, political and social authority, it is necessary to unpack how this unusual scientific project emerged from the flourishing social sciences, how it relied on the evidential power of medical sciences, but also how epidemiology was embedded in late-imperial state craft and driven by a powerful sanitary utopianism.

This historical approach will raise a set of questions: What was the point of concern around which epidemiological reasoning developed? What was and is an epidemic? Or, in the language of some historians of science, what is the epistemic thing around which epidemiological reasoning established experimental systems? It is a curious fact that the noun ‘epidemy’ has all but disappeared from use in English. While French and German – like many other languages – continue to refer to epidemics as a noun (eg. épidémie, Epdiemie) the adjective epidemic has come to stand in as a noun in the English-speaking world. This raises a series of intriguing questions, especially as the noun ‘epidemy’ vanishes precisely in the same period when epidemiology becomes a formal discipline.

With a focus on the epidemic as an object of knowledge, the project asks where the boundaries of this object are in the long twentieth century. Originally defined, modelled and surveyed in communicable diseases, the frame of an epidemic quickly expands into a range of different medical specialties as well as returned into the social sciences. From psychiatric epidemiology in the 1950s over the epidemics of smoking, heart disease and obesity to genetic epidemiology; reasoning about questions of health and disease with an epidemiological lens assumed astonishing prominence.

With the development of data science, epidemiological reasoning becomes supercharged into a leading scientific exercise. But also beyond medical applications, ‘epidemics’ are used to frame, analyse and understand social phenomena. The epidemic seemed to hold insights that the social sciences and humanities could not deliver. Analyses of violence and rioting, considerations of innovations and rumours as well as the timely surveillance of vaccine hesitancy, all became subject to epidemiological reasoning.

The project will trace these multiple translations in epidemiological reasoning and the expansion of the epidemy as a frame of analysis through three discrete themes: modelling, correlation, and configuration. The first theme, Modelling and the history of the epidemiological graph seeks to reconstruct the biographies of models and modelling practices to understand the intellectual currents and theoretical contributions to epidemiological reasoning. The second theme, Correlation, and the Making of Epidemiological Data, will turn to the data practices that established the infrastructures of the thriving field in national and global institutions, to understand how discrete paper technologies structure and inform epidemiological reasoning. The third theme, Configuration, and the Formation of Interdisciplinary Expertise will map out the transdisciplinary networks of the field to understand who at what time and under which circumstances was entrusted with the provision of epidemiological expertise (especially as these were rarely card-carrying epidemiologists)

Project description

Themes Description

Themes

Modelling

The theme will analyse how stochastic epidemiological modelling endowed epidemiology with scientific status, and how mathematical methods won the discipline unprecedented authority. Akin to Morgan’s history of economics (2012), the theme will historically reconstruct the conditions in which epidemiological theories and models were developed, and trace the emergence of epidemic standard models. Archival research will produce a series of biographies of epidemiology’s standard models, such as the Reed-Frost Epidemic Theory. The case studies envisioned for the theme will focus on late-nineteenth-century modelling of epidemic distribution curves in rodent populations, the development of ecological models (Méthot 2012; 2019) in the interwar years, and consider models designed to suggest causal association from strong correlations. Further, the theme will investigate the transfer of models between population demography (Kingsland 2005), cybernetics (Pias 2016) and epidemiological theory. 

We will chart bibliometric indices to track the legacy of specific models in and beyond traditional epidemiological literature to develop a systematic account of the wider impact of epidemiological reasoning. Case studies might focus on the reception and uptake of models in the nascent field of psychiatric epidemiology in the mid-20th century to animate the conflicts between epidemiology’s data scientific approaches and psychiatry’s traditional reliance on patient cases. This work will cover the arrival of principles of contagion in psychiatry and illuminate the impact of epidemiological methods, such as in the Epidemiological Catchment Area project in 1977 (Fuhrer and Robins 2007) up to contemporary examples in suicide prevention in the digital ecosystem (Marks 2019).

 
 
Modelling

Correlation

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.

Archival research will systematise the paper technologies and narrative conventions which epidemiologists used to forge inferences from scattered case data regarding a vast array of environmental variables (climate, housing, human-animal relations) with medical understandings of a specific disease. Historical case studies will include the narrative genre of epidemiological outbreak reporting (e.g. Bubonic Plague 1894-1959; Influenza 1918), standardised international mortality registers (Institut Pasteur, League of Nations’ Health Bureau, PAHO), forms and tables for social surveys and examples of geographical reconnaissance (e.g. malaria campaigns).

 
Correlation

Configuration

 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. We will conduct qualitative and quantitative discourse analyses to map reference networks and grasp the disciplinary flexibility in epidemiological publications and journals. Comprehensive bibliometric mapping of social and epistemic networks in epidemiology will reveal novel connections to inform a series of case studies which will illuminate the open-ended configuration of epidemiology as a generalist science.

 
Configuration