Senior Researcher in Statistical Genetics and Pathogen Dynamics
After a PhD and some postdoctoral research in theoretical particle physics, I joined the group of Christophe Fraser, at Imperial College London 2014-2016, and at the Big Data Institute since. I research the evolutionary epidemiology of viruses: how they spread, how they change, and how they damage our health. My publications are here*.
Before the pandemic, I mostly worked on the BEEHIVE project: analysing HIV genetic data, together with clinical data about the individuals with those viruses, to better understand how differences in the virus (encoded in its genetics) affect infection severity. I wrote the tools shiver for reconstructing HIV (and other viral) genomes from short pieces of DNA, and phyloscanner (with Matthew Hall and Christophe) for analysing within- and between-host pathogen genetic diversity. Here are some slides about shiver and phyloscanner and related ideas; here's a webinar in which I go through some of those slides.
Since January 2020 I've mostly been working on COVID-19, in particular using mathematical and statistical modelling to understand how helpful digital contact tracing (using mobile phone apps) is. We first proposed using this new public health intervention for COVID-19 here and first evaluated its effect on slowing viral spread here. Read more about our group's COVID-19 work here.
While at Imperial I lectured Core Mathematics for masters courses in public health and epidemiology. Here's some material I wrote for this: the quiz testing all of the material covered, and the answers; basic manipulation of numbers - the slides for 2015 and prose-style notes from 2014; inequalities, functions and units - slides for 2015, solutions to the problems, and prose-style notes from 2014; probability parts one and two; calculus in more detail; a bit of supplementary material about trigonometric, exponential and logarithmic functions, and matrices.
Assorted useful links:
- Read this if you write in English. Read this if you write in order to make a point.
- Read this if you give talks.
- Read this if you're a scientist using a computer.
- These resources were recommended for learning to use the command line (a.k.a. the terminal a.k.a. the shell), which is an important step in being able to use other people's computational scientific methods: http://rik.smith-unna.com/command_line_bootcamp
- This was highly recommended for learning version control with Git (aimed at users of R but with more general applicability).
- This helps one remember obscure latex symbols.
Here are some bash commands (i.e. working with the terminal / command line) that I find helpful.
*(This link provides open access to my only publication that's paywalled, on academic institutional policy on flying: Jean and Wymant, Science 2019.)
OpenABM-Covid19-An agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing.
Hinch R. et al, (2021), PLoS computational biology, 17
The epidemiological impact of the NHS COVID-19 app.
Wymant C. et al, (2021), Nature, 594, 408 - 412
Time to evaluate COVID-19 contact-tracing apps.
Colizza V. et al, (2021), Nat Med, 27, 361 - 362
Epidemiological changes on the Isle of Wight after the launch of the NHS Test and Trace programme: a preliminary analysis.
Kendall M. et al, (2020), The Lancet. Digital health, 2, e658 - e666
A Comprehensive Genomics Solution for HIV Surveillance and Clinical Monitoring in Low-Income Settings.
Bonsall D. et al, (2020), Journal of clinical microbiology, 58