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dc.contributor.authorDykes, Jason
dc.contributor.authorAbdul-Rahman, Alfie
dc.contributor.authorArchambault, Daniel
dc.contributor.authorBach, Benjamin
dc.contributor.authorBorgo, Rita
dc.contributor.authorChen, Min
dc.contributor.authorEnright, Jessica
dc.contributor.authorFang, Hui
dc.contributor.authorFirat, Elif E
dc.contributor.authorFreeman, Euan
dc.contributor.authorGönen, Tuna
dc.contributor.authorHarris, Claire
dc.contributor.authorJianu, Radu
dc.contributor.authorJohn, Nigel W
dc.contributor.authorKhan, Saiful
dc.contributor.authorLahiff, Andrew
dc.contributor.authorLaramee, Robert S
dc.contributor.authorMatthews, Louise
dc.contributor.authorMohr, Sibylle
dc.contributor.authorNguyen, Phong H
dc.contributor.authorRahat, Alma A M
dc.contributor.authorReeve, Richard
dc.contributor.authorRitsos, Panagiotis D
dc.contributor.authorRoberts, Jonathan C
dc.contributor.authorSlingsby, Aidan
dc.contributor.authorSwallow, Ben
dc.contributor.authorTorsney-Weir, Thomas
dc.contributor.authorTurkay, Cagatay
dc.contributor.authorTurner, Robert
dc.contributor.authorVidal, Franck P
dc.contributor.authorWang, Qiru
dc.contributor.authorWood, Jo
dc.contributor.authorXu, Kai
dc.identifier.citationDykes , J , Abdul-Rahman , A , Archambault , D , Bach , B , Borgo , R , Chen , M , Enright , J , Fang , H , Firat , E E , Freeman , E , Gönen , T , Harris , C , Jianu , R , John , N W , Khan , S , Lahiff , A , Laramee , R S , Matthews , L , Mohr , S , Nguyen , P H , Rahat , A A M , Reeve , R , Ritsos , P D , Roberts , J C , Slingsby , A , Swallow , B , Torsney-Weir , T , Turkay , C , Turner , R , Vidal , F P , Wang , Q , Wood , J & Xu , K 2022 , ' Visualization for epidemiological modelling : challenges, solutions, reflections and recommendations ' , Philosophical Transactions of the Royal Society. A, Mathematical, Physical and Engineering Sciences , vol. 380 , no. 2233 , 20210299 .
dc.identifier.otherPURE: 281141822
dc.identifier.otherPURE UUID: db404427-3644-4afc-a67d-008d14387a1c
dc.identifier.otherPubMed: 35965467
dc.identifier.otherPubMedCentral: PMC9376715
dc.identifier.otherORCID: /0000-0002-0227-2160/work/118411944
dc.identifier.otherScopus: 85136540559
dc.descriptionThis work was supported in part by the UKRI/EPSRC grant nos. EP/V054236/1 and EP/V033670/1 and UKRI/STFC grant no. ST/V006126/1.en
dc.description.abstractWe 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. See
dc.relation.ispartofPhilosophical Transactions of the Royal Society. A, Mathematical, Physical and Engineering Sciencesen
dc.rightsCopyright © 2022 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License, which permits unrestricted use, provided the original author and source are credited.en
dc.subjectVisual analyticsen
dc.subjectEpidemiological modellingen
dc.subjectComputational notebooksen
dc.subjectVisual designen
dc.subjectHA Statisticsen
dc.subjectRA0421 Public health. Hygiene. Preventive Medicineen
dc.subjectSDG 3 - Good Health and Well-beingen
dc.titleVisualization for epidemiological modelling : challenges, solutions, reflections and recommendationsen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.description.statusPeer revieweden

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