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The Importance of Scaling for an Agent Based Model: An Illustrative Case Study with COVID-19 in Zimbabwe

Wise, S; Milusheva, S; Ayling, S; (2022) The Importance of Scaling for an Agent Based Model: An Illustrative Case Study with COVID-19 in Zimbabwe. In: Proceedings of the International Conference on Computational Science 2022. (pp. pp. 259-265). Springer Nature Green open access

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Abstract

Agent-based models frequently make use of scaling techniques to render the simulated samples of population more tractable. The degree to which this scaling has implications for model forecasts, however, has yet to be explored; in particular, no research on the spatial implications of this has been done. This work presents a simulation of the spread of Covid-19 among districts in Zimbabwe and assesses the extent to which results vary relative to the samples upon which they are based. It is determined that in particular, different geographical dynamics of the spread of disease are associated with varying population sizes, with implications for others seeking to use scaled populations in their research.

Type: Proceedings paper
Title: The Importance of Scaling for an Agent Based Model: An Illustrative Case Study with COVID-19 in Zimbabwe
Event: ICCS 2022 - International Conference on Computational Science
ISBN-13: 9783031087530
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-031-08754-7_35
Publisher version: https://doi.org/10.1007/978-3-031-08754-7_35
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: Agent-based modelling, Scaling, Synthetic population, Agent-based modeling, Simulation
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10153491
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