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. 2023 Nov 14;18(11):e0293416.
doi: 10.1371/journal.pone.0293416. eCollection 2023.

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

Mario Saviano  1 , Annalisa Fierro  2 , Antonella Liccardo  1
Affiliations

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

Mario Saviano et al. PLoS One. .

Abstract

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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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Fluxes diagram.
Fig 2
Fig 2. Comparison between the daily incidence predicted by the model and that observed experimentally.
Fig 3
Fig 3. Comparison between the daily prevalence predicted by the model and that observed experimentally.
Fig 4
Fig 4
Main: Comparison between the cumulative number of recovered individuals (from November 15, 2021) predicted by the model (detected and total) and that observed experimentally. Inset: Fraction of undetected recovered individuals. Dashed line represents the mean value.
Fig 5
Fig 5. Comparison between the cumulative number of deaths (from November 15, 2021) predicted by the model and that observed experimentally.
Fig 6
Fig 6
Main: Trends (predicted by the model) of incidence in the vaccinated population and the unvaccinated population by number of individuals belonging to the two subgroups. Inset: ratio between unvaccinated and vaccinated incidence.
Fig 7
Fig 7. Comparison among the incidence in different scenarios.
Fig 8
Fig 8. Range of change in prevalence, in response to perturbation of eo¯(t) in the region [eo¯(t)·98%,eo¯(t)·102%].
Fig 9
Fig 9. Range of change in cumulative number of deaths, in response to perturbation of eo¯(t) in the region [eo¯(t)·98%,eo¯(t)·102%].
See this image and copyright information in PMC

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Supplementary concepts