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Dr Thibaut Jombart

MRC Centre for Outbreak Analysis and Modelling
Department of Infectious Disease Epidemiology
Imperial College
St Mary’s Campus
Norfolk Place
London W2 1PG
United Kingdom
Tel. : 0044 (0)20 7594 3658
thibautjombart_AT_gmail.com
 

  I am a lecturer in biostatistics and genetic analysis in the MRC Center for Outbreak Analysis and Modelling, Imperial College London. 

I am interested in developing new methods and tools for understanding how infectious disease spread, and how they can be contained. 
The methodological approaches I use include likelihood approaches, Bayesian statisticsmultivariate methods, graph theory, spatial statistics, and phylogenetics, and all involve the R software, for which I developed a number of packages. I am heading the R Epidemics Consortium (RECON: http://repidemicsconsortium.org), an initiative for the development of R tools for outbreak analysis and response.

The list below details most of my current research interests.


Finding who infects whom
Since 2009, I have been developing new methods (seqTrack, outbreaker) for disease outbreaks using genome sequences of pathogens. My current work focusses on integrating various types of
epidemiological and genetic data to reconstruct transmission trees. The related package, outbreaker2, will provide a new framework for unifying different approaches of source imputation.

Emergency outbreak response
I have been involved first-hand in several outbreak responses, including the 2009 pandemic influenza, and the Middle-East Respiratory Syndrome (MERS), and more recently as a member of the WHO Ebola response team since August 2014. Numerous tools are needed for such responses, from data collection, encryption and cleaning to advanced statistical modelling and interactive visualisation. I believe that this toolbox is best developed collectively, by bringing together elite modellers, software developers and public health officers. Since 2013, I have been organising international hackathons to foster such collaborations (hackout, hackout2). The most recent one is Hackout 3, the most ambitious event to date, hosted in Berkeley (CA) in June 2016.

Automated outbreak detection
In collaboration with Public Health England (PHE) and several colleagues at Imperial College, I am developing new approaches for detecting outbreaks from genomic surveillance databases. This project relies on integrating full genome sequences alongside spatio-temporal data using graph theory and statistics. The related package vimes is hosted on github.

Forensics of food-borne disease outbreaks
In collaboration with the Gastro-intestinal Bacterial Reference Unit (GBRU) at PHE, I am developing new tools to input the origins of food-borne disease outbreaks using full genome sequence data and partial information on the food distribution network. 
The related package dibbler is hosted on github.

Genetic data analysis
I am also interested in population genetics and phylogenetics. I am the author of adegenet, a package which has become a standard for the statistical analysis of genetic and genomic data in R. I am also a core developer of other packages, including adephylo (phylogenetic signal), apex (phylogenetics with multiple genes) and treescape, a new package for the analysis of phylogenetic incongruence. For the last few years, I have been running various forms of a short course on genetic data analysis using R, currently through PR statistics.