Julia Ledien
PhD
Postdoctoral Researcher in Infectious Disease and Spatial Analysis
I joined the Chami Group in May 2022 to work on SchistoTrack project, a cohort project designed to study different aspects of schistosomiasis epidemiology in Uganda. The parasite causing the disease is acquired during contact with contaminated water as the parasite enters the body through the skin. The contamination of the water occurs when infected urine or faeces are brought into water sites where certain species of freshwater snails are present. Using a modelling pipeline based on machine learning and spatial analyses, I am bringing together multimodal data to classify water sites based on ecological aspects, as well as individual usage and anthropological factors to build granular models for the force-of-infection of schistosomiasis.
I did a 2-year MPH program specialising in International Health at ISPED in Bordeaux, France. After a 6-months MPH internship in the Epidemiology and Public Health Unit of the Pasteur Institute in Cambodia where I worked on risk-mapping for leptospirosis, I took on a role as an epidemiologist for the ECOMORE project. This project aimed to document and model the progression of epidemics along roads, using dengue as a proxy. In 2018, I undertook a PhD at the University of Sussex to estimate the spatiotemporal variation in Chagas disease exposure and burden of disease. My expertise lies in spatial and spatiotemporal epidemiology of neglected tropical diseases.
Recent publications
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Spatiotemporal variations in exposure: Chagas disease in Colombia as a case study
Journal article
Ledien J. et al, (2022), BMC Medical Research Methodology, 22
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Linear and Machine Learning modelling for spatiotemporal disease predictions: Force-of-Infection of Chagas disease
Journal article
Ledien J. et al, (2022), PLOS Neglected Tropical Diseases, 16, e0010594 - e0010594
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An algorithm applied to national surveillance data for the early detection of major dengue outbreaks in Cambodia
Journal article
Ledien J. et al, (2019), PLOS ONE, 14, e0212003 - e0212003
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Assessing the performance of remotely-sensed flooding indicators and their potential contribution to early warning for leptospirosis in Cambodia.
Journal article
Ledien J. et al, (2017), PLoS One, 12