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Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations

Jason Dykes Orcid Logo, Alfie Abdul-Rahman Orcid Logo, Daniel Archambault Orcid Logo, Benjamin Bach Orcid Logo, Rita Borgo Orcid Logo, Min Chen Orcid Logo, Jessica Enright, Hui Fang, Elif E. Firat Orcid Logo, Euan Freeman Orcid Logo, Tuna Gönen Orcid Logo, Claire Harris Orcid Logo, Radu Jianu Orcid Logo, Nigel W. John Orcid Logo, Saiful Khan, Andrew Lahiff Orcid Logo, Robert S. Laramee, Louise Matthews Orcid Logo, Sibylle Mohr Orcid Logo, Phong H. Nguyen, Alma Rahat Orcid Logo, Richard Reeve Orcid Logo, Panagiotis D. Ritsos Orcid Logo, Jonathan C. Roberts Orcid Logo, Aidan Slingsby Orcid Logo, Ben Swallow Orcid Logo, Tom Torsney-Weir Orcid Logo, Cagatay Turkay Orcid Logo, Robert Turner, Franck P. Vidal Orcid Logo, Qiru Wang Orcid Logo, Jo Wood Orcid Logo, Kai Xu Orcid Logo

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Volume: 380, Issue: 2233

Swansea University Authors: Daniel Archambault Orcid Logo, Rita Borgo Orcid Logo, Alma Rahat Orcid Logo, Tom Torsney-Weir Orcid Logo

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DOI (Published version): 10.1098/rsta.2021.0299

Abstract

We report on an ongoing collaboration between epidemiological modellers and visualization researchers by documenting and reflecting upon knowledge constructs—a series of ideas, approaches and methods taken from existing visualization research and practice—deployed and developed to support modelling...

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Published in: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
ISSN: 1364-503X 1471-2962
Published: The Royal Society 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa59890
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Abstract: We report on an ongoing collaboration between epidemiological modellers and visualization researchers by documenting and reflecting upon knowledge constructs—a series of ideas, approaches and methods taken from existing visualization research and practice—deployed and developed to support modelling of the COVID-19 pandemic. Structured independent commentary on these efforts is synthesized through iterative reflection to develop: evidence of the effectiveness and value of visualization in this context; open problems upon which the research communities may focus; guidance for future activity of this type and recommendations to safeguard the achievements and promote, advance, secure and prepare for future collaborations of this kind. In describing and comparing a series of related projects that were undertaken in unprecedented conditions, our hope is that this unique report, and its rich interactive supplementary materials, will guide the scientific community in embracing visualization in its observation, analysis and modelling of data as well as in disseminating findings. Equally we hope to encourage the visualization community to engage with impactful science in addressing its emerging data challenges. If we are successful, this showcase of activity may stimulate mutually beneficial engagement between communities with complementary expertise to address problems of significance in epidemiology and beyond.
Keywords: visualization, visual analytics, epidemiologicalmodelling, computational notebooks, visualdesign
College: College of Science
Funders: RAMP VIS: Making Visual Analytics an Integral Part of the Technological Infrastructure for Combating COVID-19 Funder: Engineering and Physical Sciences Research Council (EPSRC) Visual Analytics for Explaining and Analysing Contact Tracing Networks Funder: Engineering and Physical Sciences Research Council (EPSRC)
Issue: 2233