OATAO - Open Archive Toulouse Archive Ouverte Open Access Week

Analogies between SARS-CoV-2 infection dynamics and batch chemical reactor behavior

Manenti, Flavio and Galeazzi, A. and Bisotti, F. and Prifti, K. and Dell'Angelo, A. and Di Pretoro, Alessandro and Ariatti, C. Analogies between SARS-CoV-2 infection dynamics and batch chemical reactor behavior. (2020) Chemical Engineering Science, 227. 115918. ISSN 0009-2509

[img]
Preview
(Document in English)

PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
956kB

Official URL: https://doi.org/10.1016/j.ces.2020.115918

Abstract

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 beassumed to be molecules of chemical compounds and their dynamics seem well aligned with those ofcomposition and conversions in chemical syntheses. Thanks to these analogies, it is possible to generatepandemic predictive models based on chemical and physical considerations and regress their kineticparameters, either globally or locally, to predict the peak time, entity and end of the infection with certainreliability. These predictions can strongly support the emergency plans decision making process. Themodel predictions have been validated with data from Chinese provinces that already underwent com-plete infection dynamics. For all the other countries, the evolution is re-regressed and re-predicted everyday, updating a pandemic prediction database on Politecnico di Milano’s webpage based on the real-timeavailable data.

Item Type:Article
HAL Id:hal-03081865
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Other partners > Politecnico di Milano (ITALY)
Laboratory name:
Funders:
Centre for Sustainable Process Engineering Research (SuPER) at Politecnico di Milano
Statistics:download
Deposited On:18 Dec 2020 11:49

Repository Staff Only: item control page