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Trystan Leng

About Me

I am a PDRA as part of the JUNIPER consortium, and a PhD student at the Mathematics for Real-World Systems Centre for Doctoral Training (currently in the process of submission).

My research focuses on understanding the importance of including contact network structure in epidemiological models, and constructing models that incorporate this structure to answer pressing real-world questions. My PhD focused on the importance of including network structure in models of the spread and control of sexually transmitted infections. More recently, I have developed models to understand the impact of social bubbles and school reopening strategies in the context of COVID-19.

Outside of mathematics, I have a keen interest in the history and philosophy of science.

Current Research

My current research explores the impact of secondary school reopening reopening strategies on COVID-19 transmission and absences. We compare strategies involving rapid testing using lateral flow device tests (LFTs) to strategies involving isolating year-group bubbles. A preprint of our work is available here. Currently, I am considering the impact of uptake and adherence on the success of such strategies.


MSc Mathematics of Systems (Distinction) - University of Warwick (2016-2017)
BSc Mathematics & Philosophy (1st Class) - University of Glasgow (2011-2015)
Thomas G Holt Prize for Logic (2014)


Leng, T., White, C., Hilton, J., Kucharski, A., Pellis, L., Stage, H., Davies, N.G., Keeling, M.J. and Flasche, S., 2020. The effectiveness of social bubbles as part of a Covid-19 lockdown exit strategy, a modelling study. Wellcome Open Research, 5(213), p.213.

Keeling, M.J., Hill, E.M., Gorsich, E.E., Penman, B., Guyver-Fletcher, G., Holmes, A., Leng, T., McKimm, H., Tamborrino, M., Dyson, L. and Tildesley, M.J., 2021. Predictions of COVID-19 dynamics in the UK: short-term forecasting and analysis of potential exit strategies. PLoS computational biology, 17(1), p.e1008619.

Leng, T. and Keeling, M.J., 2020. Improving pairwise approximations for network models with susceptible-infected-susceptible dynamics. Journal of Theoretical Biology, 500, p.110328.

Leng, T. and Keeling, M.J., 2018. Concurrency of partnerships, consistency with data, and control of sexually transmitted infections. Epidemics, 25, pp.35-46.

Leng, T., Leng, G. and MacGregor, D.J., 2017. Spike patterning in oxytocin neurons: Capturing physiological behaviour with Hodgkin-Huxley and integrate-and-fire models. PloS one, 12(7), p.e0180368.


Leng, T., Hill, E.M., Thompson, R.N., Tildesley, M.J., Keeling, M.J. and Dyson, L., 2021. Assessing the impact of secondary school reopening strategies on within-school COVID-19 transmission and absences: a modelling study. medRxiv.

Southall, E.R., Holmes, A., Hill, E.M., Atkins, B.D., Leng, T., Thompson, R.N., Dyson, L.J., Keeling, M.J. and Tildesley, M., 2021. An analysis of school absences in England during the Covid-19 pandemic. MedRxiv.


The underlying code for my COVID-19 research concerning social bubbles and secondary school reopening strategies is accessible via GitHub.

Conferences, Summer Schools, Workshops

- Network Modelling for Epidemics Workshop (University of Washington, August 2019)

- Infectious Disease Dynamics Conference (Ambleside, September 2018)

- European Conference on Mathematical and Theoretical Biology (Lisbon, July 2018)

- Introduction to Machine Learning Summer School (University of Warwick, June 2017)

- BioDynamics Workshop (University of Exeter, September 2016)

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