Trystan Leng
Trystan graduated in 2021 with a PhD in Mathematics for Real-World Systems.
Following his viva, Trystan was a Postdoctoral Research Associate in the JUNIPER consortium.
Trystan's 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. His PhD focused on the importance of including network structure in models of the spread and control of sexually transmitted infections. More recently, Trystan developed models to understand the impact of social bubbles and school reopening strategies in the context of COVID-19 (preprints of the group's work are available here and here).
Outside of mathematics, Trystan's interests include the history and philosophy of science.
Education
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)
Publications
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.
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. BMC Medicine.
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.
Pre-prints
Leng, T., Hill, E.M., Keeling, M.J., Tildesley, M.J. and Thompson, R.N., 2021. The effect of notification window length on the epidemiological impact of COVID-19 contact tracing mobile applications. medRxiv.
Leng, T., Hill, E.M., Holmes, A., Southall, E., Thompson, R.N., Tildesley, M.J., Keeling, M.J. and Dyson, L., 2021. Quantifying within-school SARS-CoV-2 transmission and the impact of lateral flow testing in secondary schools in England. medRxiv.
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.
GitHub
The underlying code for my COVID-19 research concerning social bubbles and secondary school reopening strategies is accessible via GitHub.
Blog posts on my research
Exiting lockdown - are social bubbles an effective strategy? - Trystan Leng, Wellcome Open Research Blog, 27/4/21
Testing testing in schools - Rachel Thomas, +plus magazine, 4/3/21
Conferences, Summer Schools, Workshops
- V-KEMS Unlocking Higher Education Virtual Study Group (Isaac Newton Institute, June 2020)
- 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)
