Diagnostic Tests and Epidemiological Obfuscation

26 October 2021, 14:00 - 16:00

Online event (UK time)

This is an online event hosted via Zoom. Registration is required for this event.



Speaker

Alice Street (University of Edinburgh)
Ritti Soncco (University of Edinburgh)
Aphaluck Bhatiasevi (University of Edinburgh)

 

Abstract

Diagnostics and Epidemiological Obfuscation

Epidemiology and laboratory medicine have a long, often contentious relationship. Yet, epidemiological knowledge also depends, fundamentally, on laboratory testing: to enable case detection, point-source identification, and disease tracking. Epidemiologists often employ rapid diagnostic tests in the field, and/or send samples to the laboratory for analysis and confirmation. National disease profiles are often collated from diagnostic data collected in clinical facilities, and depends on the capacity of clinical laboratories to carry out disease-specific tests. The availability and design of diagnostic tests therefore have an outsized influence on what epidemiologists are able to know.

Diagnostic testing is often associated with medical visibility; it facilitates the medical gaze and makes population-level disease mapping possible. In this seminar, by contrast, we will explore what diagnostic tests conceal about the burden and dynamics of disease in the population. One facet of diagnostic obfuscation relates to the absence of diagnostic infrastructure and resources, either in particular places or for specific diseases, rendering whole diseases and populations data-invisible. Another facet relates to the design of diagnostic tests themselves, and how processes of technical optimisation can conceal as well as reveal aspects of disease. We will explore these issues through three case studies of diagnosis for 'neglected' diseases: Onchocerciasis, Melioidosis, and Lyme Disease.

The development of rapid diagnostic tools for Onchocerciasis have been driven by elimination goals for the disease. Drawing on collaborative research undertaken with Emma M. Taylor, Alice Street will discuss how the optimisation of a novel test for specific elimination use-cases simultaneously occluded other kinds of epidemiological applications, and in doing so contributed to uncertainties about the public health value of the tool.

Lyme disease diagnosis in the UK has become a site of contested epidemiologies, with patient groups citing what they see as poor diagnostic tests for the widespread under-diagnosis and under-reporting of the disease. In this presentation Ritti Soncco describes how patient advocates contest the dependence of formal epidemiological knowledge on a limited number of government authorised tests and put forward their own epidemiological claims, based on their informal ‘mapping’ of the disease through social networks and private laboratory testing rather than NHS based testing. At stake in the uncertain sensitivity of approved diagnostic tests are questions of how prevalent the disease is in the population, whether chronic Lyme exists, and also, since Lyme is caused by infection with bacteria that is transmitted to humans by ticks, how safe is the British landscape.

Melioidosis is a bacterial disease transmitted to humans by contact with contaminated water or soil. Despite its often devastating impact on marginalised communities in Southeast Asia and Northern Australia, the disease receives little attention from the wider global health community. In this presentation, Aphaluck Bhatiasevi explores the role of diagnostic testing in the production of Melioidosis’s invisibility. The most common diagnostic methods for both clinical management and research entail bacterial culture of human specimens. But by focusing on disease in the human body, such methods potentially lead to the concealment of the wider presence of the pathogen in the environment, raising the question of how alternative testing methods could support an environmental epidemiology of melioidosis.

 

 

An event organised by Hidden Epidemics and Epidemiological Obfuscation Research Network
Administrative assistance: networks@crassh.cam.ac.uk 


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