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An interactive tool for enhancing hospital capacity predictions using an epidemiological model

F. Gibson, R. Fabbro, Alma Rahat Orcid Logo, T. Torsney-Weir, D. Archambault, Michael Gravenor Orcid Logo, Biagio Lucini Orcid Logo

Proceedings of the Genetic and Evolutionary Computation Conference Companion

Swansea University Authors: Alma Rahat Orcid Logo, Michael Gravenor Orcid Logo, Biagio Lucini Orcid Logo

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DOI (Published version): 10.1145/3449726.3462738

Abstract

Hospital managers have limited resources, and they have to plan on how best to allocate these resources based on predicted demand, which is often based on linear or exponential models. In this paper, we propose an interactive tool that produces a forecast of bed occupancy based on an epidemiological...

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Published in: Proceedings of the Genetic and Evolutionary Computation Conference Companion
ISBN: 978-1-4503-8351-6 978-1-4503-8351-6
Published: New York, NY, USA ACM 2021
Online Access: http://dx.doi.org/10.1145/3449726.3462738
URI: https://cronfa.swan.ac.uk/Record/cronfa64016
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first_indexed 2023-09-18T10:23:52Z
last_indexed 2023-09-18T10:23:52Z
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spelling v2 64016 2023-08-02 An interactive tool for enhancing hospital capacity predictions using an epidemiological model 6206f027aca1e3a5ff6b8cd224248bc2 0000-0002-5023-1371 Alma Rahat Alma Rahat true false 70a544476ce62ba78502ce463c2500d6 0000-0003-0710-0947 Michael Gravenor Michael Gravenor true false 7e6fcfe060e07a351090e2a8aba363cf 0000-0001-8974-8266 Biagio Lucini Biagio Lucini true false 2023-08-02 SCS Hospital managers have limited resources, and they have to plan on how best to allocate these resources based on predicted demand, which is often based on linear or exponential models. In this paper, we propose an interactive tool that produces a forecast of bed occupancy based on an epidemiological model. We optimise this model to fit recently observed data, and interactivity is conferred through a controllable parameter of the model such that users can readily investigate hypothetical scenarios for planning purposes. This study was designed with the Welsh National Health Service, and was born out of their practical need of accurately modelling hospital occupancy during the ongoing Covid-19 pandemic. Conference Paper/Proceeding/Abstract Proceedings of the Genetic and Evolutionary Computation Conference Companion ACM New York, NY, USA 978-1-4503-8351-6 978-1-4503-8351-6 7 7 2021 2021-07-07 10.1145/3449726.3462738 http://dx.doi.org/10.1145/3449726.3462738 Editor: Francisco Chicano COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2023-09-18T11:29:38.7643413 2023-08-02T14:54:33.4618716 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science F. Gibson 1 R. Fabbro 2 Alma Rahat 0000-0002-5023-1371 3 T. Torsney-Weir 4 D. Archambault 5 Michael Gravenor 0000-0003-0710-0947 6 Biagio Lucini 0000-0001-8974-8266 7
title An interactive tool for enhancing hospital capacity predictions using an epidemiological model
spellingShingle An interactive tool for enhancing hospital capacity predictions using an epidemiological model
Alma Rahat
Michael Gravenor
Biagio Lucini
title_short An interactive tool for enhancing hospital capacity predictions using an epidemiological model
title_full An interactive tool for enhancing hospital capacity predictions using an epidemiological model
title_fullStr An interactive tool for enhancing hospital capacity predictions using an epidemiological model
title_full_unstemmed An interactive tool for enhancing hospital capacity predictions using an epidemiological model
title_sort An interactive tool for enhancing hospital capacity predictions using an epidemiological model
author_id_str_mv 6206f027aca1e3a5ff6b8cd224248bc2
70a544476ce62ba78502ce463c2500d6
7e6fcfe060e07a351090e2a8aba363cf
author_id_fullname_str_mv 6206f027aca1e3a5ff6b8cd224248bc2_***_Alma Rahat
70a544476ce62ba78502ce463c2500d6_***_Michael Gravenor
7e6fcfe060e07a351090e2a8aba363cf_***_Biagio Lucini
author Alma Rahat
Michael Gravenor
Biagio Lucini
author2 F. Gibson
R. Fabbro
Alma Rahat
T. Torsney-Weir
D. Archambault
Michael Gravenor
Biagio Lucini
format Conference Paper/Proceeding/Abstract
container_title Proceedings of the Genetic and Evolutionary Computation Conference Companion
publishDate 2021
institution Swansea University
isbn 978-1-4503-8351-6
978-1-4503-8351-6
doi_str_mv 10.1145/3449726.3462738
publisher ACM
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
url http://dx.doi.org/10.1145/3449726.3462738
document_store_str 0
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description Hospital managers have limited resources, and they have to plan on how best to allocate these resources based on predicted demand, which is often based on linear or exponential models. In this paper, we propose an interactive tool that produces a forecast of bed occupancy based on an epidemiological model. We optimise this model to fit recently observed data, and interactivity is conferred through a controllable parameter of the model such that users can readily investigate hypothetical scenarios for planning purposes. This study was designed with the Welsh National Health Service, and was born out of their practical need of accurately modelling hospital occupancy during the ongoing Covid-19 pandemic.
published_date 2021-07-07T11:29:40Z
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score 11.017797

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