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Title: Exploring the integration of traditional and molecular epidemiological methods for infectious disease outbreaks
Author: Coltart, Cordelia Emma Maitland
ISNI:       0000 0004 7230 9234
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2018
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BACKGROUND: Understanding the transmission dynamics of infectious pathogens is critical to developing effective public health strategies. Traditionally, time consuming epidemiological methods were used, often limited by incomplete or inaccurate datasets. Novel phylogenetic techniques can determine transmission events, but have rarely been used in real-time outbreak settings to inform interventions and limit the impact of outbreaks. METHODS: I undertook a series of novel studies to explore the utility of combining phylogenetics with traditional epidemiological analysis to enhance the understanding of transmission dynamics. I investigated HIV in an endemic South African setting and Ebola in an acute outbreak in Sierra Leone. The strengths and limitations of this combined approach are explored, ethical issues investigated and recommendations made regarding the implications of this work for public health. RESULTS: Phylogenetics provides an exciting and synergistic tool to epidemiological analysis in outbreak investigation and control. These combined methods enable a more detailed understanding than is possible through either discipline alone. My key findings include: • Identification of infection source: Phylogenetics gives new insight into the role of external introductions (e.g. migrators) in driving and sustaining the high incidence of HIV. • Earlier identification of new emerging clusters: I identified a new cluster of HIV from around a mining community. This is one of the first examples of molecular methods detecting a previously unknown outbreak. • Identification of novel mechanisms of transmission: This work suggests that children may have been infected by playing in puddles contaminated with Ebola, a previously unrecognised route of transmission. CONCLUSION: The integration of these two methods facilitate sophisticated real-time techniques to maximise understanding of transmission dynamics, allowing faster and more effectively targeted interventions. Moving forwards, sequence data should be incorporated into standard outbreak investigation. This is critical at a time when infectious disease outbreaks have led to the some of the most significant global health threats of the recent past.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available