Diagnostics without diagnosis: RDTs for Sleeping Sickness in Uganda

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Diagnosing sleeping sickness (also known as human African trypanosomiasis (HAT)) is complicated, requiring the alignment of clinical suspicion with serological, parasitological, and molecular confirmation to determine appropriate treatment. Previously, diagnosis was carried out by mobile lab teams which confirmed cases in village screenings and transported patients for treatment. Since cases have declined however, expensive active screening campaigns have been phased out and replaced with passive, symptom-based algorithms. Without early treatment sleeping sickness is fatal, yet timely diagnosis in regional referral hospitals is difficult to access for many of the remote, rural communities predominantly affected. Rapid Diagnostic Tests (RDTs) are designed to be affordable, portable and easy-to-use; desirable attributes in resource-poor settings, and favourable in disease elimination conditions where case numbers are low and dispersed across remote areas.

In 2013, an RDT-based passive surveillance strategy was implemented in Uganda to spearhead an intensified T.b. gambiense HAT elimination programme. The finger-prick test developed by FIND with academic, manufacturing and national control programme partners, detects antibodies in fresh blood samples against two trypanosome antigens. It ostensibly requires minimal training of health workers and produces a positive or negative result within 15 minutes. Tests provided by FIND were delivered through the national elimination programme to frontline health facilities as part of a new sleeping sickness diagnostic algorithm, to be conducted when symptomatic patients tested RDT negative for malaria. As the elimination programme area is also endemic for malaria, staff at all facilities were already familiar with performing malaria RDTs. This familiarity prefigured the implementation of an RDT for sleeping sickness and it was assumed the test could be absorbed seamlessly into a pre-established diagnostic routine.

Malaria and HAT RDTs have shared aesthetic features (pictured), but how similar are their social lives? Post testing, the diagnostic processes they initiate significantly diverge. Owing to the potentially toxic nature of HAT drugs, treatment cannot be administered based on clinical suspicion or RDT results alone, and patients must travel to hospital for follow-up tests (microscopy, PCR, and if still positive, lumbar puncture). This can be disappointing for patients, and confusing when negative follow-up tests contradict initial positive RDT results, the most common outcome in elimination settings. For patients contemplating the costs and benefits of completing HAT referrals in a place where sleeping sickness is rare and it is unlikely they’ll be confirmed as ‘true’ cases in need of treatment, the implications are profound. Falling short of expectations set by the malaria model it sought to assimilate into, the HAT RDT not only fails to eliminate the need for a laboratory, but introduces additional layers of diagnosis, bureaucracy, and travel for patients and health workers. In contrast to the mobile team-led system which preceded the RDT, the diagnostic algorithm for HAT is divided across different levels of the health system and geographic spaces, requiring patients to travel between institutions by their own means. It begs the question, where does diagnosis actually occur in this system?

The hope that the sleeping sickness RDT would integrate seamlessly into the existing malaria diagnostic ecosystem was premised on a presumed similarity between the two RDTs that in fact did not extend beyond the physical features of the device itself. But diagnosis cannot be reduced to the result shown in the RDT window. It is a spatially and temporally distributed process that comprises a dynamic assemblage of infrastructures, including health information systems, supply chains, clinical expertise and, crucially, patient decision-making. Diagnostic ecosystems are as fragile as they are dynamic and complex, and new technologies can have unpredictable and destabilising effects on relationships between diagnosis and care.


Shona Jane Lee is a PhD candidate at the University of Edinburg, and a member of the multidisciplinary Investigating Networks of Zoonosis Innovations (INZI)research group at the Centre of African Studies. She holds an ESRC AQM studentship for her project on the socio-technical systems of disease control, focussing on novel technological interventions for sleeping sickness control and elimination in Uganda.

Diagnostic stories follows the emerging world of devices, instruments, protocols and machines that make up the world of global health diagnostics. Through the telling of stories about specific technological artefacts it traces the rise of diagnosis as a global health concern and offers a critical perspective on the device-focused approach of many attempts to improve diagnostic infrastructure in the Global South. The series is edited by Alice Street.

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