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

Title: Mathematical modeling of respiratory viral infection and applications to SARS‐CoV‐2 progression
Authors: Ait Mahiout, Latifa; Bessonov, Nikolai; Kazmierczak, Bogdan; Volpert, Vitaly
Contributors: Narodowe Centrum Nauki
Source: Mathematical Methods in the Applied Sciences ; volume 46, issue 2, page 1740-1751 ; ISSN 0170-4214 1099-1476
Publisher Information: Wiley
Publication Year: 2022
Collection: Wiley Online Library (Open Access Articles via Crossref)
Description: 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.
Document Type: article in journal/newspaper
Language: English
DOI: 10.1002/mma.8606
Availability: https://doi.org/10.1002/mma.8606; https://onlinelibrary.wiley.com/doi/pdf/10.1002/mma.8606; https://onlinelibrary.wiley.com/doi/full-xml/10.1002/mma.8606
Rights: http://onlinelibrary.wiley.com/termsAndConditions#vor
Accession Number: edsbas.57F813E8
Database: BASE