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., Philos Trans R Soc Lond B Biol Sci, Vol:374

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

Kamvar Z, Cai J, Pulliam JRC, et al., 2019, Epidemic curves made easy using the R package incidence


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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