Imperial College London

Miss Mélodie Monod

Faculty of Natural SciencesDepartment of Mathematics

Research Postgraduate







Huxley BuildingSouth Kensington Campus





I am a PhD student in the CDT in Modern Statistics and Statistical Machine Learning, supervised by Dr. Oliver Ratmann at Imperial and Dr. Matthew Hall at the Oxford BDI. I am interested in the development of Bayesian models to reconstruct infectious disease's connected network of sources, sinks, and hubs. These applications may help to inform public health interventions.

My PhD project focuses on reconstructing HIV-1 transmission chains from deep-sequence data gathered by the PANGEA initiative.

I am currently part of the Imperial College COVID-19 response team. We are working on real-time tracking of the COVID-19 epidemic in Europe and the US.



Faria NR, Mellan TA, Whittaker C, et al., 2021, Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil, Science, Vol:372, ISSN:0036-8075, Pages:815-+

Unwin H, Mishra S, Bradley V, et al., 2020, State-level tracking of COVID-19 in the United States, Nature Communications, Vol:11, ISSN:2041-1723, Pages:1-9

Flaxman S, Mishra S, Gandy A, et al., 2020, Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe, Nature, Vol:584, ISSN:0028-0836, Pages:257-261

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