activity
20172022
most citedVisualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations

22 citations · 32 across the 6 of their papers we have counts for

collaborators

6 papers

stat.ME2022

Data Fusion in a Two-stage Spatio-Temporal Model using the INLA-SPDE Approach

Stephen Jun Villejo, Janine B Illian, Ben Swallow

This paper proposes a two-stage estimation approach for a spatial misalignment scenario that is motivated by the epidemiological problem of linking pollutant exposures and health o…

stat.CO2022★ 1 cited

Bayesian inference for stochastic oscillatory systems using the phase-corrected Linear Noise Approximation

Ben Swallow, David A. Rand, Giorgos Minas

Likelihood-based inference in stochastic non-linear dynamical systems, such as those found in chemical reaction networks and biological clock systems, is inherently complex and has…

cs.HC2022★ 22 cited

Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations

Jason Dykes, Alfie Abdul-Rahman, Daniel Archambault +30

We report on an ongoing collaboration between epidemiological modellers and visualization researchers by documenting and reflecting upon knowledge constructs -- a series of ideas,…

stat.AP2021★ 8 cited

Tracking the national and regional COVID-19 epidemic status in the UK using directed Principal Component Analysis

Ben Swallow, Wen Xiang, Jasmina Panovska-Griffiths

One of the difficulties in monitoring an ongoing pandemic is deciding on the metric that best describes its status when multiple intercorrelated measurements are available. Having…

stat.CO2020

Parallel tempering as a mechanism for facilitating inference in hierarchical hidden Markov models

Giada Sacchi, Ben Swallow

The study of animal behavioural states inferred through hidden Markov models and similar state switching models has seen a significant increase in popularity in recent years. The a…

stat.ME2017★ 1 cited

Parametric uncertainty in complex environmental models: a cheap emulation approach for models with high-dimensional output

B. Swallow, M. Rigby, J. C. Rougier +3

In order to understand underlying processes governing environmental and physical processes, and predict future outcomes, a complex computer model is frequently required to simulate…