A deterministic compartmental model for the transition between variants in the spread of Covid-19 in Italy.

We propose a deterministic epidemic model to describe the transition between two variants of the same virus, through the combination of a series of realistic mechanisms such as partial cross immunity, waning immunity for vaccinated individuals and a novel data-based algorithm to describe the average...

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Main Authors: Mario Saviano, Annalisa Fierro, Antonella Liccardo
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2023-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0293416&type=printable
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author Mario Saviano
Annalisa Fierro
Antonella Liccardo
author_facet Mario Saviano
Annalisa Fierro
Antonella Liccardo
author_sort Mario Saviano
collection DOAJ
description We propose a deterministic epidemic model to describe the transition between two variants of the same virus, through the combination of a series of realistic mechanisms such as partial cross immunity, waning immunity for vaccinated individuals and a novel data-based algorithm to describe the average immunological status of the population. The model is validated on the evolution of Covid-19 in Italy, during the period in which the transition between Delta and Omicron variant occurred, with very satisfactory agreement with the experimental data. According to our model, if the vaccine efficacy had been equal against Delta and Omicron variant infections, the transition would have been smoothed and the epidemic would have gone extinct. This circumstance confirms the fundamental role of vaccines in combating the epidemic, and the importance of identifying vaccines capable of intercepting new variants.
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spelling doaj.art-837518b1214648a8ba223ed4364f48502023-12-12T05:34:27ZengPublic Library of Science (PLoS)PLoS ONE1932-62032023-01-011811e029341610.1371/journal.pone.0293416A deterministic compartmental model for the transition between variants in the spread of Covid-19 in Italy.Mario SavianoAnnalisa FierroAntonella LiccardoWe propose a deterministic epidemic model to describe the transition between two variants of the same virus, through the combination of a series of realistic mechanisms such as partial cross immunity, waning immunity for vaccinated individuals and a novel data-based algorithm to describe the average immunological status of the population. The model is validated on the evolution of Covid-19 in Italy, during the period in which the transition between Delta and Omicron variant occurred, with very satisfactory agreement with the experimental data. According to our model, if the vaccine efficacy had been equal against Delta and Omicron variant infections, the transition would have been smoothed and the epidemic would have gone extinct. This circumstance confirms the fundamental role of vaccines in combating the epidemic, and the importance of identifying vaccines capable of intercepting new variants.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0293416&type=printable
spellingShingle Mario Saviano
Annalisa Fierro
Antonella Liccardo
A deterministic compartmental model for the transition between variants in the spread of Covid-19 in Italy.
PLoS ONE
title A deterministic compartmental model for the transition between variants in the spread of Covid-19 in Italy.
title_full A deterministic compartmental model for the transition between variants in the spread of Covid-19 in Italy.
title_fullStr A deterministic compartmental model for the transition between variants in the spread of Covid-19 in Italy.
title_full_unstemmed A deterministic compartmental model for the transition between variants in the spread of Covid-19 in Italy.
title_short A deterministic compartmental model for the transition between variants in the spread of Covid-19 in Italy.
title_sort deterministic compartmental model for the transition between variants in the spread of covid 19 in italy
url https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0293416&type=printable
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