Imperial College London


Faculty of MedicineSchool of Public Health

Senior Lecturer



+44 (0)20 7594 3622x.didelot




G30Medical SchoolSt Mary's Campus





I am a lecturer in the Department of Infectious Disease Epidemiology within the School of Public Health at Imperial College London. I am also a member of the MRC Centre for Outbreak Analysis and Modelling and of the NIHR Health Protection Research Unit in Modelling Methodology.

Research Interests

My research is focused on the analysis of genomic data in order to improve our understanding of bacterial evolution, epidemiology, ecology and pathogenicity. A key aim is to develop new bioinformatics and statistical methods that can handle the very large amounts of data made available by novel high-throughput sequencing techniques.

Because of the interdisciplinary nature of my work, I have broad interests in a variety of subjects, including theoretical topics such as mathematical population genetics, Bayesian statistics or Monte-Carlo methods, and biological topics such as bacterial evolutionary processes or pathogen epidemiology.

I have worked on a wide range of bacterial pathogens, especially those causing healthcare associated infections (eg Clostridium difficile and Staphylococcus aureus) and gastrointestinal infections (eg Salmonella enterica, Bacillus cereusCampylobacter jejuni and Helicobacter pylori).

Biographical Sketch

In 2007, I completed a doctorate in Statistical Genetics in the Department of Statistics, University of Oxford. I then spent three years as a postdoctoral research fellow in the Department of Statistics, University of Warwick. In 2010, I moved back to the University of Oxford as a leadership fellow in genomic microbiology before taking my current appointment with Imperial College London in April 2012. For more details see my personal webpage.


I have developed the following computer software, all of which are freely available on the internet: 

ClonalFrame: inference of bacterial microevolution using sequence data
GenoPlast: analysis of genomic plasticity in bacteria
SimMLST: Simulation of genetic data under a neutral model
ClonalOrigin: inference of homologous recombination in bacteria using whole genome sequences
TransPhylo: inference of a pathogen transmission tree given a phylogeny
ClonalFrameML: efficient inference of recombination in whole bacterial genomes


I collaborate with the Modernising Medical Microbiology consortium which brings together the University of Oxford, the Health Protection Agency, the Sanger Institute and the NHS, with the aim of revolutionizing our understanding of human pathogens through the use of whole-genome sequencing technology. Three major bacterial pathogens are under particular investigation: Staphylococcus aureus, Clostridium difficile and Mycobacterium tuberculosis

Other frequent collaborators include:

Mark Achtman (University of Warwick)
Aaron Darling (University of Technology Sydney)
Daniel Falush (Swansea University)
Dan Lawson (University of Bristol)
Martin Maiden (University of Oxford)
Tim Read (Emory University)
Sam Sheppard (Swansea University)
Sebastian Suerbaum (Hannover Medical School)
Danny Wilson (University of Oxford)

Selected Publications

Journal Articles

Didelot X, Walker AS, Peto TE, et al., 2016, Within-host evolution of bacterial pathogens, Nature Reviews Microbiology, Vol:14, ISSN:1740-1526, Pages:150-162

Biek R, Pybus OG, Lloyd-Smith JO, et al., 2015, Measurably evolving pathogens in the genomic era, Trends in Ecology & Evolution, Vol:30, ISSN:0169-5347, Pages:306-313

Didelot X, Pang B, Zhou Z, et al., 2015, The Role of China in the Global Spread of the Current Cholera Pandemic, Plos Genetics, Vol:11, ISSN:1553-7404

Didelot X, Wilson DJ, 2015, ClonalFrameML: Efficient Inference of Recombination in Whole Bacterial Genomes, PLOS Computational Biology, Vol:11, ISSN:1553-734X

Croucher NJ, Didelot X, 2015, The application of genomics to tracing bacterial pathogen transmission, Current Opinion in Microbiology, Vol:23, ISSN:1369-5274, Pages:62-67

Didelot X, Gardy J, Colijn C, 2014, Bayesian Inference of Infectious Disease Transmission from Whole-Genome Sequence Data, Molecular Biology and Evolution, Vol:31, ISSN:0737-4038, Pages:1869-1879

Dingle KE, Elliott B, Robinson E, et al., 2014, Evolutionary History of the Clostridium difficile Pathogenicity Locus, Genome Biology and Evolution, Vol:6, ISSN:1759-6653, Pages:36-52

Ansari MA, Didelot X, 2014, Inference of the Properties of the Recombination Process from Whole Bacterial Genomes, Genetics, Vol:196, ISSN:1943-2631, Pages:253-+

More Publications