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Monte Carlo simulation of COVID-19 pandemic using Planck’s probability distribution
We present a Monte Carlo simulation model of an epidemic spread inspired on physics variables such as temperature, cross section and interaction range, which considers the Plank distribution of photons in the black body radiation to describe the mobility of individuals. The model consists of a latti...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9135486/ https://www.ncbi.nlm.nih.gov/pubmed/35644321 http://dx.doi.org/10.1016/j.biosystems.2022.104708 |
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author | Amaro, José Enrique Orce, José Nicolás |
author_facet | Amaro, José Enrique Orce, José Nicolás |
author_sort | Amaro, José Enrique |
collection | PubMed |
description | We present a Monte Carlo simulation model of an epidemic spread inspired on physics variables such as temperature, cross section and interaction range, which considers the Plank distribution of photons in the black body radiation to describe the mobility of individuals. The model consists of a lattice of cells that can be in four different states: susceptible, infected, recovered or death. An infected cell can transmit the disease to any other susceptible cell within some random range [Formula: see text]. The transmission mechanism follows the physics laws for the interaction between a particle and a target. Each infected particle affects the interaction region a number [Formula: see text] of times, according to its energy. The number of interactions is proportional to the interaction cross section [Formula: see text] and to the target surface density [Formula: see text]. The discrete energy follows a Planck distribution law, which depends on the temperature [Formula: see text] of the system. For any interaction, infection, recovery and death probabilities are applied. We investigate the results of viral transmission for different sets of parameters and compare them with available COVID-19 data. The parameters of the model can be made time dependent in order to consider, for instance, the effects of lockdown in the middle of the pandemic. |
format | Online Article Text |
id | pubmed-9135486 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91354862022-05-31 Monte Carlo simulation of COVID-19 pandemic using Planck’s probability distribution Amaro, José Enrique Orce, José Nicolás Biosystems Article We present a Monte Carlo simulation model of an epidemic spread inspired on physics variables such as temperature, cross section and interaction range, which considers the Plank distribution of photons in the black body radiation to describe the mobility of individuals. The model consists of a lattice of cells that can be in four different states: susceptible, infected, recovered or death. An infected cell can transmit the disease to any other susceptible cell within some random range [Formula: see text]. The transmission mechanism follows the physics laws for the interaction between a particle and a target. Each infected particle affects the interaction region a number [Formula: see text] of times, according to its energy. The number of interactions is proportional to the interaction cross section [Formula: see text] and to the target surface density [Formula: see text]. The discrete energy follows a Planck distribution law, which depends on the temperature [Formula: see text] of the system. For any interaction, infection, recovery and death probabilities are applied. We investigate the results of viral transmission for different sets of parameters and compare them with available COVID-19 data. The parameters of the model can be made time dependent in order to consider, for instance, the effects of lockdown in the middle of the pandemic. Elsevier B.V. 2022-08 2022-05-27 /pmc/articles/PMC9135486/ /pubmed/35644321 http://dx.doi.org/10.1016/j.biosystems.2022.104708 Text en © 2022 Elsevier B.V. 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 | Article Amaro, José Enrique Orce, José Nicolás Monte Carlo simulation of COVID-19 pandemic using Planck’s probability distribution |
title | Monte Carlo simulation of COVID-19 pandemic using Planck’s probability distribution |
title_full | Monte Carlo simulation of COVID-19 pandemic using Planck’s probability distribution |
title_fullStr | Monte Carlo simulation of COVID-19 pandemic using Planck’s probability distribution |
title_full_unstemmed | Monte Carlo simulation of COVID-19 pandemic using Planck’s probability distribution |
title_short | Monte Carlo simulation of COVID-19 pandemic using Planck’s probability distribution |
title_sort | monte carlo simulation of covid-19 pandemic using planck’s probability distribution |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9135486/ https://www.ncbi.nlm.nih.gov/pubmed/35644321 http://dx.doi.org/10.1016/j.biosystems.2022.104708 |
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