PhD defence by Cecilie Thystrup

Principal supervisor:

• Professor Tine Hald

Co-supervisor:

• Senior Researcher Sara Monteiro Pires
• Associate Professor Thomas Nordahl Petersen
• Senior Researcher Patrick Murigu Kamau Njage

Examiners:

• Senior researcher Ana Sofia Ribeiro Duarte, DTU Food
• Senior Reseacher Henrik Hasman, SSI
• Professor Eric Fevre, ILRI, University of Liverpool

Chairperson at defence:

• Senior Researcher Morten Poulsen, DTU Food

Resume
Each year, nearly one in ten people fall ill to diseases caused by consuming contaminated food and water, resulting in severe health consequences, economic loss, and strain on healthcare systems. The World Health Organization (WHO) estimates that the largest burden of disease is carried by sub-Saharan Africa, where particularly children under five are affected. One of the critical issues with foodborne diseases (FBDs) in low- and middle-income countries (LMICs) is the limited understanding of the epidemiology and disease dynamics within these settings, which makes it difficult to identify major sources of infection and implement effective control measures. Addressing these issues requires strong surveillance systems that can generate actionable data, but surveillance efforts in LMICs often fall short due to limited infrastructure and resources. New technologies have emerged in recent years, which has opened the door for the implementation of genome-based surveillance in LMICs.

In light of these new opportunities, this PhD project set out to explore how technologies like whole genome sequencing (WGS) and metagenomics could help improve the detection and understanding of FBDs in African LMICs. Through four manuscripts, this PhD thesis investigated how genomic tools like metagenomics and WGS can improve FBD surveillance in African LMICs. The work explored the use of metagenomic data from feces, wastewater, and other sources for identifying pathogens in real-world surveillance settings (Manuscript I). It also examined the sources and risk factors of foodborne infections in children under five (Manuscript II), developed new methods for source tracking using low-abundance genomic data (Manuscript III), and analyzed the structural and behavioral challenges limiting the effectiveness of current FBD surveillance systems, offering suggestions for future improvements (Manuscript IV).

The findings from the thesis indicate that while technical capacity is improving, the successful implementation of genomic methods in LMIC settings depends on more than sequencing technologies alone. Surveillance systems should reflect local conditions and be backed by infrastructure, cross-sector collaboration, and long-term political support. Investments in portable sequencing, cloud tools, and community-based models can strengthen surveillance and early outbreak detection.

A copy of the PhD thesis is available for reading at the department.