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).
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).
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.