PhD Studentship: Transforming Disease Monitoring in the Era of Home Diagnostics
Project Overview
Gastrointestinal (GI) infections remain a major public health challenge in the United Kingdom and worldwide. Robust monitoring is essential for detecting outbreaks, tackling trends and informing timely interventions. Traditionally, this has relied on laboratory testing following referral of samples by general practitioners and hospital clinicians. For every single case diagnosed and reported to national surveillance in this way, there are nearly 150 community cases occurring under the public health radar.
A major shift is underway. The rapid growth of at-home diagnostic kits by-passes the bottleneck of conventional face-to-face appointments by enabling individuals to test for infections outside conventional healthcare services. These technologies are generating new, potentially valuable data streams but their role in public health monitoring remains largely unexplored.
This PhD offers a rare opportunity to study this transformation as it unfolds, and to explore the hidden burden of GI infections. You will investigate whether data from home diagnostics can enhance monitoring systems, expose the submerged portion of the disease iceberg, and reshape how infectious diseases are monitored in the future.
Aims and Methods
This interdisciplinary project sits at the intersection of public health, microbiology and social science addressing the question: Can home diagnostic testing meaningfully improve monitoring of gastrointestinal infections?
The project will be tailored to your interests, likely including:
- Technology and market analysis: evaluating available home diagnostic kits, including pathogens detected and technologies used.
- Understanding users and behaviours: conducting social science research (e.g. surveys or interviews) to understand who uses these tests and how this influences the data produced.
- Public health integration: analysing whether and how these data could support existing monitoring, including identifying biases and data gaps.
The project will deliver a forward-looking framework to support the integration of home diagnostic data into public health monitoring.
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