Anagnostou, A;
Groen, D;
Taylor, SJE;
Suleimenova, D;
Abubakar, N;
Saha, A;
Mintram, K;
... Anokye, N; + view all
(2023)
FACS-CHARM: A Hybrid Agent-Based and Discrete-Event Simulation Approach for Covid-19 Management at Regional Level.
In:
Proceedings - Winter Simulation Conference.
(pp. pp. 1223-1234).
IEEE: Singapore.
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Abstract
Pandemics have huge impact on all aspect of people's lives. As we have experienced during the Coronavirus pandemic, healthcare, education and the economy have been put under extreme strain. It is important therefore to be able to respond to such events fast in order to limit the damage to the society. Decision-makers typically are advised by experts in order to inform their response strategies. One of the tools that is widely used to support evidence-based decisions is modeling and simulation. In this paper, we present a hybrid agent-based and discrete-event simulation for the Coronavirus pandemic management at regional level. Our model considers disease dynamics, population interactions and dynamic ICU bed capacity management and predicts the impact of various public health preventive measures on the population and the healthcare service.
| Type: | Proceedings paper |
|---|---|
| Title: | FACS-CHARM: A Hybrid Agent-Based and Discrete-Event Simulation Approach for Covid-19 Management at Regional Level |
| Event: | 2022 Winter Simulation Conference (WSC) |
| Location: | SINGAPORE, Singapore |
| Dates: | 11 Dec 2022 - 14 Dec 2022 |
| ISBN-13: | 9798350309713 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/WSC57314.2022.10015462 |
| Publisher version: | http://dx.doi.org/10.1109/wsc57314.2022.10015462 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Science & Technology, Technology, Physical Sciences, Computer Science, Theory & Methods, Operations Research & Management Science, Mathematics, Applied, Computer Science, Mathematics |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10187277 |
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