Imperial College London

DrThibautJombart

Faculty of MedicineSchool of Public Health

Senior Lecturer
 
 
 
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Contact

 

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

 
 
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Location

 

UG11Norfolk PlaceSt Mary's Campus

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Summary

 

Summary

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.

Publications

Journals

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

Dighe A, Jombart T, Van Kerkhove MD, et al., 2019, A systematic review of MERS-CoV seroprevalence and RNA prevalence in dromedary camels: implications for animal vaccination, Epidemics, Vol:29, ISSN:1755-4365

Thompson R, Stockwin J, van Gaalen R, et al., 2019, Improved inference of time-varying reproduction numbers during infectious disease outbreaks, Epidemics, Vol:29, ISSN:1755-4365, Pages:1-11

Moraga P, Dorigatti I, Kamvar ZN, et al., 2019, epiflows: an R package for risk assessment of travel-related spread of disease, F1000research, Vol:7, Pages:1374-1374

Moraga P, Dorigatti I, Kamvar ZN, et al., 2019, epiflows: an R package for risk assessment of travel-related spread of disease, F1000research, Vol:7, Pages:1374-1374

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