BioMathematics Seminar
Ben Swalow (University of St. Andrews, United Kingdom)
19th December | 14:00-15:00 | Library auditorium
online: https://videoconf-
Title: Spatial and temporal statistical analyses of infectious disease spread and outcomes.
Abstract: Throughout the COVID-19 pandemic, statisticians and modellers have been called on to help inform multiple aspects of pandemic response and scientific understanding. This has highlighted many challenges in making fast decisions under uncertainty, some of which remain unsolved. In this talk I will outline some of the approaches I have used to help assist with understanding the state and properties of the SARS-CoV-2 pandemic in the UK, from approaches to comparing trends between nations, to estimating the relative transmission rates of different variants of concern. All aim to extract useful information from noisy, high-dimensional and ever-changing data.
Short Bio: Ben Swallow is currently a Lecturer (Research and Education) in Statistics, School of Mathematics and Statistics, University of St Andrews. His research interests lie largely in Bayesian statistical inference, particularly Markov chain Monte Carlo (MCMC) methods, including model selection with reversible jump MCMC. BS is also interested in inference for stochastic dynamical systems of biological and environmental processes, such as those found in population ecology, cell-signalling and infectious diseases. These are often represented using state-space models and variants. Additionally, BS worked extensively in models for continuous data with many exact zeros and integrating multivariate data from varying sources and supports, which incorporate those interests above. Finally, BS has interests in real-world applications of the above spanning biological and ecological sciences. His work frequently involves collaborations with domain experts and data collectors in these fields.