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Analogies between SARS-CoV-2 infection dynamics and batch chemical reactor behavior
The pandemic infection of SARS-CoV-2 presents analogies with the behavior of chemical reactors. Susceptible population (A), active infected population (B), recovered cases (C) and deaths (D) can be assumed to be molecules of chemical compounds and their dynamics seem well aligned with those of compo...
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/PMC7305736/ https://www.ncbi.nlm.nih.gov/pubmed/32834062 http://dx.doi.org/10.1016/j.ces.2020.115918 |
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author | Manenti, F. Galeazzi, A. Bisotti, F. Prifti, K. Dell'Angelo, A. Di Pretoro, A. Ariatti, C. |
author_facet | Manenti, F. Galeazzi, A. Bisotti, F. Prifti, K. Dell'Angelo, A. Di Pretoro, A. Ariatti, C. |
author_sort | Manenti, F. |
collection | PubMed |
description | The pandemic infection of SARS-CoV-2 presents analogies with the behavior of chemical reactors. Susceptible population (A), active infected population (B), recovered cases (C) and deaths (D) can be assumed to be molecules of chemical compounds and their dynamics seem well aligned with those of composition and conversions in chemical syntheses. Thanks to these analogies, it is possible to generate pandemic predictive models based on chemical and physical considerations and regress their kinetic parameters, either globally or locally, to predict the peak time, entity and end of the infection with certain reliability. These predictions can strongly support the emergency plans decision making process. The model predictions have been validated with data from Chinese provinces that already underwent complete infection dynamics. For all the other countries, the evolution is re-regressed and re-predicted every day, updating a pandemic prediction database on Politecnico di Milano’s webpage based on the real-time available data. |
format | Online Article Text |
id | pubmed-7305736 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73057362020-06-22 Analogies between SARS-CoV-2 infection dynamics and batch chemical reactor behavior Manenti, F. Galeazzi, A. Bisotti, F. Prifti, K. Dell'Angelo, A. Di Pretoro, A. Ariatti, C. Chem Eng Sci Short Communication The pandemic infection of SARS-CoV-2 presents analogies with the behavior of chemical reactors. Susceptible population (A), active infected population (B), recovered cases (C) and deaths (D) can be assumed to be molecules of chemical compounds and their dynamics seem well aligned with those of composition and conversions in chemical syntheses. Thanks to these analogies, it is possible to generate pandemic predictive models based on chemical and physical considerations and regress their kinetic parameters, either globally or locally, to predict the peak time, entity and end of the infection with certain reliability. These predictions can strongly support the emergency plans decision making process. The model predictions have been validated with data from Chinese provinces that already underwent complete infection dynamics. For all the other countries, the evolution is re-regressed and re-predicted every day, updating a pandemic prediction database on Politecnico di Milano’s webpage based on the real-time available data. Elsevier Ltd. 2020-12-14 2020-06-20 /pmc/articles/PMC7305736/ /pubmed/32834062 http://dx.doi.org/10.1016/j.ces.2020.115918 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 | Short Communication Manenti, F. Galeazzi, A. Bisotti, F. Prifti, K. Dell'Angelo, A. Di Pretoro, A. Ariatti, C. Analogies between SARS-CoV-2 infection dynamics and batch chemical reactor behavior |
title | Analogies between SARS-CoV-2 infection dynamics and batch chemical reactor behavior |
title_full | Analogies between SARS-CoV-2 infection dynamics and batch chemical reactor behavior |
title_fullStr | Analogies between SARS-CoV-2 infection dynamics and batch chemical reactor behavior |
title_full_unstemmed | Analogies between SARS-CoV-2 infection dynamics and batch chemical reactor behavior |
title_short | Analogies between SARS-CoV-2 infection dynamics and batch chemical reactor behavior |
title_sort | analogies between sars-cov-2 infection dynamics and batch chemical reactor behavior |
topic | Short Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305736/ https://www.ncbi.nlm.nih.gov/pubmed/32834062 http://dx.doi.org/10.1016/j.ces.2020.115918 |
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