Imperial College London


Faculty of MedicineSchool of Public Health

Senior Lecturer



+44 (0)20 7594 3658t.jombart Website




UG11Norfolk PlaceSt Mary's Campus





I am a biometrician working on statistical genetics of pathogen populations. I am currently working as a research associate with Neil Ferguson, Christophe Fraser and Simon Cauchemez. My work aims to develop novel statistical approaches for extracting information from pathogen genomes and gain insights into the spatio-temporal dynamics of infectious diseases. The methodological approaches I use include multivariate analysis, Bayesian statisticsspatial statisticsgraph theory, and phylogenetics. I am also interested in using simulations to understand which and how biological processes shape the genetic diversity observed in biological populations.


I am also extensively involved with the development of free software for the analysis of genetic and epidemiological data. I have recently organized a R hackathon on disease outbreak modelling using molecular data, hosted by the MRC Center for Outbreak Analysis and Modelling in January 2013

I am author or contributor for the following R packages:

- adegenet (author): multivariate analysis for genetic/genomic data

- adephylo (author): tools for testing and describing the  phylogenetic signal

- geoGraph (author): large-scale modelling of spatial data

- ade4 (contributor): multivariate analysis, graphics, spatial statistics

phylobase (contributor): handling and analyses of phylogenetic comparative data

- sedaR (contributor): spatial statistics for ecological data

- outbreaker (author): Bayesian reconstruction of disease outbreaks using genomic data

- epibase (author): basic tools for the disease outbreak analysis



More information is available from my  webpage.



Brooks-Pollock E, Danon L, Jombart T, et al., 2021, Modelling that shaped the early COVID-19 pandemic response in the UK., Philos Trans R Soc Lond B Biol Sci, Vol:376

Jombart T, Ghozzi S, Schumacher D, et al., 2021, Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection., Philos Trans R Soc Lond B Biol Sci, Vol:376

Jit M, Jombart T, Nightingale ES, et al., 2020, Estimating number of cases and spread of coronavirus disease (COVID-19) using critical care admissions, United Kingdom, February to March 2020, Eurosurveillance, Vol:25, ISSN:1025-496X, Pages:6-10

Jombart T, Jarvis CI, Mesfin S, et al., 2020, The cost of insecurity: from flare-up to control of a major Ebola virus disease hotspot during the outbreak in the Democratic Republic of the Congo, 2019, Eurosurveillance, Vol:25, ISSN:1560-7917, Pages:19-22

Jombart T, van Zandvoort K, Russell TW, et al., 2020, Inferring the number of COVID-19 cases from recently reported deaths., Wellcome Open Res, Vol:5, ISSN:2398-502X

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