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Spreading of infections on random graphs: A percolation-type model for COVID-19
We introduce an epidemic spreading model on a network using concepts from percolation theory. The model is motivated by discussing the standard SIR model, with extensions to describe effects of lockdowns within a population. The underlying ideas and behaviour of the lattice model, implemented using...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7332959/ https://www.ncbi.nlm.nih.gov/pubmed/32834619 http://dx.doi.org/10.1016/j.chaos.2020.110077 |
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author | Croccolo, Fabrizio Roman, H. Eduardo |
author_facet | Croccolo, Fabrizio Roman, H. Eduardo |
author_sort | Croccolo, Fabrizio |
collection | PubMed |
description | We introduce an epidemic spreading model on a network using concepts from percolation theory. The model is motivated by discussing the standard SIR model, with extensions to describe effects of lockdowns within a population. The underlying ideas and behaviour of the lattice model, implemented using the same lockdown scheme as for the SIR scheme, are discussed in detail and illustrated with extensive simulations. A comparison between both models is presented for the case of COVID-19 data from the USA. Both fits to the empirical data are very good, but some differences emerge between the two approaches which indicate the usefulness of having an alternative approach to the widespread SIR model. |
format | Online Article Text |
id | pubmed-7332959 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73329592020-07-06 Spreading of infections on random graphs: A percolation-type model for COVID-19 Croccolo, Fabrizio Roman, H. Eduardo Chaos Solitons Fractals Frontiers We introduce an epidemic spreading model on a network using concepts from percolation theory. The model is motivated by discussing the standard SIR model, with extensions to describe effects of lockdowns within a population. The underlying ideas and behaviour of the lattice model, implemented using the same lockdown scheme as for the SIR scheme, are discussed in detail and illustrated with extensive simulations. A comparison between both models is presented for the case of COVID-19 data from the USA. Both fits to the empirical data are very good, but some differences emerge between the two approaches which indicate the usefulness of having an alternative approach to the widespread SIR model. Elsevier Ltd. 2020-10 2020-07-03 /pmc/articles/PMC7332959/ /pubmed/32834619 http://dx.doi.org/10.1016/j.chaos.2020.110077 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Frontiers Croccolo, Fabrizio Roman, H. Eduardo Spreading of infections on random graphs: A percolation-type model for COVID-19 |
title | Spreading of infections on random graphs: A percolation-type model for COVID-19 |
title_full | Spreading of infections on random graphs: A percolation-type model for COVID-19 |
title_fullStr | Spreading of infections on random graphs: A percolation-type model for COVID-19 |
title_full_unstemmed | Spreading of infections on random graphs: A percolation-type model for COVID-19 |
title_short | Spreading of infections on random graphs: A percolation-type model for COVID-19 |
title_sort | spreading of infections on random graphs: a percolation-type model for covid-19 |
topic | Frontiers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7332959/ https://www.ncbi.nlm.nih.gov/pubmed/32834619 http://dx.doi.org/10.1016/j.chaos.2020.110077 |
work_keys_str_mv | AT croccolofabrizio spreadingofinfectionsonrandomgraphsapercolationtypemodelforcovid19 AT romanheduardo spreadingofinfectionsonrandomgraphsapercolationtypemodelforcovid19 |