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

Geismar C, Nguyen V, Fragaszy E, et al., 2022, Bayesian reconstruction of household transmissions to infer the serial interval of COVID-19 by variants of concern: analysis from a prospective community cohort study (Virus Watch)., Lancet, Vol:400 Suppl 1

Evans B, Jombart T, 2022, Worldwide routine immunisation coverage regressed during the first year of the COVID-19 pandemic, Vaccine, Vol:40, ISSN:0264-410X, Pages:3531-3535

Waites W, Pearson CAB, Gaskell KM, et al., 2022, Transmission dynamics of SARS-CoV-2 in a strictly-Orthodox Jewish community in the UK., Sci Rep, Vol:12

Jarvis CI, Gimma A, Finger F, et al., 2022, Measuring the unknown: An estimator and simulation study for assessing case reporting during epidemics., Plos Comput Biol, Vol:18

Lindsey BB, Villabona-Arenas CJ, Campbell F, et al., 2022, Characterising within-hospital SARS-CoV-2 transmission events using epidemiological and viral genomic data across two pandemic waves (vol 13, pg 1013, 2022), Nature Communications, Vol:13

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