Synthetic Population Catalyst : a micro-simulated population of England with circadian activities
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The Synthetic Population Catalyst (SPC) is an open-source tool for the simulation of populations. Building on previous efforts, synthetic populations can be created for any area in England, from a small geographical unit to the entire country, and linked to geolocalised daily activities. In contrast to most transport models, the output is focussed on the population itself and the way people socially interact together, rather than on a precise modelling of the volume of transport trips from one area to another. SPC is therefore particularly well suited, for example, to study the spread of a pandemic within a population. Other applications include identifying segregation patterns and potential causes of inequality of opportunity amongst individuals. It is fast, thanks to its Rust codebase. The outputs for each lieutenancy area in England are directly available without having to run the code.
Salat , H , Carlino , D , Benitez-Paez , F , Zanchetta , A , Arribas-Bel , D & Birkin , M 2023 , ' Synthetic Population Catalyst : a micro-simulated population of England with circadian activities ' , Environment and Planning B: Urban Analytics and City Science , vol. OnlineFirst . https://doi.org/10.1177/23998083231203066
Environment and Planning B: Urban Analytics and City Science
Copyright © 2023 the Authors. This work has been made available online in accordance with the Rights Retention Strategy This accepted manuscript is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The final published version of this work is available at https://doi.org/10.1177/23998083231203066.Copyright © The Author(s) 2023. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
DescriptionFunding: This work was supported by Wave 1 of The UKRI Strategic Priorities Fund under the EPSRC Grant EP/W006022/1, particularly the “Ecosystem of Digital Twin” and “Shocks and Resilience” themes within that grant & The Alan Turing Institute.
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