Paper short abstract:

Drawing from the example of the East African Medical Survey, this paper considers mathematical statistics in the context of late-colonial modernism. Unlike the descriptive statistics then common in epidemiology, the affordances of mathematical statistics transformed what was doable with what data.

Paper long abstract:

The East African Medical Survey (EAMS) began in the mid 1940s to survey the health of the villages providing labour for the ill-fated Tanganyika Groundnut Scheme. This attempt to mechanise groundnut cultivation over several million acres—then one of the more costly failures of late-colonial modernism—soon fell apart but the EAMS remained, instead shifting toward the mapping and selective elimination of disease across the wider region. Six locations in Kenya and Tanganyika were selected, and thousands of people fell under detailed and invasive medical surveillance. Over the course of six years, researchers collected anthropometric and dietary data; stool, urine, blood, and skin samples; and demographic data from interviews with the many women surveyed. The correlation of social and biological data, and the construction of proxy indices from disparate data sources, was all part of the project’s stated purpose: to detail ‘a complete picture of what actually is medically wrong with the African.’ This paper considers the application of mathematical statistics as an important element of these surveys, and as a novel aspect of late-colonial modernism. In contrast to the descriptive statistics which had, until this point, dominated epidemiological and demographic surveillance in the British Empire, the application of more advanced statistical methods transformed what was doable with what data. As this paper will show, the onset of highly targeted population health interventions throughout the later twentieth century only became doable due to the statistical advances developed, in part, by the EAMS.