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Simulation of pandemics in real cities: enhanced and accurate digital laboratories
This study develops a modelling framework for simulating the spread of infectious diseases within real cities. Digital copies of Birmingham (UK) and Bogotá (Colombia) are generated, reproducing their urban environment, infrastructure and population. The digital inhabitants have the same statistical...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7897638/ https://www.ncbi.nlm.nih.gov/pubmed/33633493 http://dx.doi.org/10.1098/rspa.2020.0653 |
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author | Alexiadis, A. Albano, A. Rahmat, A. Yildiz, M. Kefal, A. Ozbulut, M. Bakirci, N. Garzón-Alvarado, D. A. Duque-Daza, C. A. Eslava-Schmalbach, J. H. |
author_facet | Alexiadis, A. Albano, A. Rahmat, A. Yildiz, M. Kefal, A. Ozbulut, M. Bakirci, N. Garzón-Alvarado, D. A. Duque-Daza, C. A. Eslava-Schmalbach, J. H. |
author_sort | Alexiadis, A. |
collection | PubMed |
description | This study develops a modelling framework for simulating the spread of infectious diseases within real cities. Digital copies of Birmingham (UK) and Bogotá (Colombia) are generated, reproducing their urban environment, infrastructure and population. The digital inhabitants have the same statistical features of the real population. Their motion is a combination of predictable trips (commute to work, school, etc.) and random walks (shopping, leisure, etc.). Millions of individuals, their encounters and the spread of the disease are simulated by means of high-performance computing and massively parallel algorithms for several months and a time resolution of 1 minute. Simulations accurately reproduce the COVID-19 data for Birmingham and Bogotá both before and during the lockdown. The model has only one adjustable parameter calculable in the early stages of the pandemic. Policymakers can use our digital cities as virtual laboratories for testing, predicting and comparing the effects of policies aimed at containing epidemics. |
format | Online Article Text |
id | pubmed-7897638 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Royal Society Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-78976382021-02-24 Simulation of pandemics in real cities: enhanced and accurate digital laboratories Alexiadis, A. Albano, A. Rahmat, A. Yildiz, M. Kefal, A. Ozbulut, M. Bakirci, N. Garzón-Alvarado, D. A. Duque-Daza, C. A. Eslava-Schmalbach, J. H. Proc Math Phys Eng Sci Research Article This study develops a modelling framework for simulating the spread of infectious diseases within real cities. Digital copies of Birmingham (UK) and Bogotá (Colombia) are generated, reproducing their urban environment, infrastructure and population. The digital inhabitants have the same statistical features of the real population. Their motion is a combination of predictable trips (commute to work, school, etc.) and random walks (shopping, leisure, etc.). Millions of individuals, their encounters and the spread of the disease are simulated by means of high-performance computing and massively parallel algorithms for several months and a time resolution of 1 minute. Simulations accurately reproduce the COVID-19 data for Birmingham and Bogotá both before and during the lockdown. The model has only one adjustable parameter calculable in the early stages of the pandemic. Policymakers can use our digital cities as virtual laboratories for testing, predicting and comparing the effects of policies aimed at containing epidemics. The Royal Society Publishing 2021-01 2021-01-27 /pmc/articles/PMC7897638/ /pubmed/33633493 http://dx.doi.org/10.1098/rspa.2020.0653 Text en © 2021 The Authors. http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/http://creativecommons.org/licenses/by/4.0/http://creativecommons.org/licenses/by/4.0/http://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Research Article Alexiadis, A. Albano, A. Rahmat, A. Yildiz, M. Kefal, A. Ozbulut, M. Bakirci, N. Garzón-Alvarado, D. A. Duque-Daza, C. A. Eslava-Schmalbach, J. H. Simulation of pandemics in real cities: enhanced and accurate digital laboratories |
title | Simulation of pandemics in real cities: enhanced and accurate digital laboratories |
title_full | Simulation of pandemics in real cities: enhanced and accurate digital laboratories |
title_fullStr | Simulation of pandemics in real cities: enhanced and accurate digital laboratories |
title_full_unstemmed | Simulation of pandemics in real cities: enhanced and accurate digital laboratories |
title_short | Simulation of pandemics in real cities: enhanced and accurate digital laboratories |
title_sort | simulation of pandemics in real cities: enhanced and accurate digital laboratories |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7897638/ https://www.ncbi.nlm.nih.gov/pubmed/33633493 http://dx.doi.org/10.1098/rspa.2020.0653 |
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