Mathematical modeling of respiratory viral infection and applications to SARS-CoV-2 progression.

SARS‐CoV‐2 variants reaction‐diffusion equations spreading speed viral infection viral load

Journal

Mathematical methods in the applied sciences
ISSN: 0170-4214
Titre abrégé: Math Methods Appl Sci
Pays: Germany
ID NLM: 9888551

Informations de publication

Date de publication:
03 Aug 2022
Historique:
received: 26 02 2022
revised: 19 07 2022
accepted: 20 07 2022
entrez: 17 10 2022
pubmed: 18 10 2022
medline: 18 10 2022
Statut: aheadofprint

Résumé

Viral infection in cell culture and tissue is modeled with delay reaction-diffusion equations. It is shown that progression of viral infection can be characterized by the viral replication number, time-dependent viral load, and the speed of infection spreading. These three characteristics are determined through the original model parameters including the rates of cell infection and of virus production in the infected cells. The clinical manifestations of viral infection, depending on tissue damage, correlate with the speed of infection spreading, while the infectivity of a respiratory infection depends on the viral load in the upper respiratory tract. Parameter determination from the experiments on Delta and Omicron variants allows the estimation of the infection spreading speed and viral load. Different variants of the SARS-CoV-2 infection are compared confirming that Omicron is more infectious and has less severe symptoms than Delta variant. Within the same variant, spreading speed (symptoms) correlates with viral load allowing prognosis of disease progression.

Identifiants

pubmed: 36247228
doi: 10.1002/mma.8606
pii: MMA8606
pmc: PMC9538414
doi:

Types de publication

Journal Article

Langues

eng

Informations de copyright

© 2022 John Wiley & Sons, Ltd.

Déclaration de conflit d'intérêts

This work does not have any conflicts of interest.

Références

Math Methods Appl Sci. 2022 Aug 03;:
pubmed: 36247228
Eur Respir J. 1992 Apr;5(4):477-87
pubmed: 1563506
Nat Rev Immunol. 2022 Jun;22(6):339-352
pubmed: 34646033
Nat Commun. 2021 Jul 16;12(1):4354
pubmed: 34272374
J Theor Biol. 2015 May 7;372:81-8
pubmed: 25746843
Front Immunol. 2020 Aug 07;11:1949
pubmed: 32849654
J Virol. 2005 Dec;79(24):15511-24
pubmed: 16306622
J Virol. 2009 Jul;83(14):7151-65
pubmed: 19439465
Biophys J. 1992 Jun;61(6):1540-9
pubmed: 1617137
Elife. 2021 Sep 27;10:
pubmed: 34569939
Cell Mol Immunol. 2021 Jul;18(7):1628-1630
pubmed: 33927362
PLoS One. 2011 Mar 24;6(3):e14767
pubmed: 21455300
Nat Commun. 2020 Oct 30;11(1):5493
pubmed: 33127906
Rev Med Virol. 2014 Sep;24(5):308-15
pubmed: 24737708
Vet Pathol. 2022 Jul;59(4):578-585
pubmed: 34794359
J Infect Dis. 2021 Oct 28;224(8):1316-1324
pubmed: 34302469
Virus Evol. 2021 Apr 27;7(1):veab039
pubmed: 34221452
J Med Virol. 2020 Apr;92(4):424-432
pubmed: 31981224
Microb Risk Anal. 2020 Dec;16:100140
pubmed: 32984489
Thorax. 2022 Feb;77(2):203-209
pubmed: 34404754

Auteurs

Latifa Ait Mahiout (L)

Laboratoire d'équations aux dérivées partielles non linéaires et histoire des mathématiques Ecole Normale Supérieure Algiers Algeria.

Nikolai Bessonov (N)

Institute of Problems of Mechanical Engineering Russian Academy of Sciences Saint Petersburg Russia.

Bogdan Kazmierczak (B)

Institute of Fundamental Technological Research Polish Academy of Sciences Warsaw Poland.

Vitaly Volpert (V)

Institut Camille Jordan, UMR 5208 CNRS University Lyon 1 Villeurbanne France.
Peoples' Friendship University of Russia 6 Miklukho-Maklaya St Moscow Russia.

Classifications MeSH