Conference Paper/Proceeding/Abstract 325 views
An interactive tool for enhancing hospital capacity predictions using an epidemiological model
Proceedings of the Genetic and Evolutionary Computation Conference Companion
Swansea University Authors:
Alma Rahat , Michael Gravenor
, Biagio Lucini
Full text not available from this repository: check for access using links below.
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...
Published in: | Proceedings of the Genetic and Evolutionary Computation Conference Companion |
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ISBN: | 978-1-4503-8351-6 978-1-4503-8351-6 |
Published: |
New York, NY, USA
ACM
2021
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Online Access: |
http://dx.doi.org/10.1145/3449726.3462738 |
URI: | https://cronfa.swan.ac.uk/Record/cronfa64016 |
first_indexed |
2023-09-18T10:23:52Z |
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last_indexed |
2024-11-25T14:13:16Z |
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cronfa64016 |
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SURis |
fullrecord |
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2023-09-18T11:29:38.7643413 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 MACS 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 Mathematics and Computer Science School COLLEGE CODE MACS 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 |
active_str |
0 |
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 |
2021-07-07T08:13:55Z |
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1824382187192975360 |
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11.052532 |