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.



Polonsky JA, Baidjoe A, Kamvar ZN, et al., 2019, Outbreak analytics: a developing data science for informing the response to emerging pathogens, Philosophical Transactions B: Biological Sciences, Vol:374, ISSN:0962-8436

Leiva C, Taboada S, Kenny NJ, et al., 2019, Population substructure and signals of divergent adaptive selection despite admixture in the sponge Dendrilla antarctica from shallow waters surrounding the Antarctic Peninsula., Mol Ecol

Campbell F, Cori A, Ferguson N, et al., 2019, Bayesian inference of transmission chains using timing of symptoms, pathogen genomes and contact data, Plos Computational Biology, Vol:15


Dighe A, Jombart T, van Kerkhove M, et al., 2019, A mathematical model of the transmission of middle East respiratory syndrome coronavirus in dromedary camels (Camelus dromedarius), ELSEVIER SCI LTD, Pages:1-1, ISSN:1201-9712


Jombart T, Kamvar ZN, Cai J, et al., 2019, reconhub/incidence: Incidence version 1.7.0, v.1.7.0

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