Artículo

Modelling the interplay of SARS-CoV-2 variants in the United Kingdom

Barreiro, Nadia Luisina ; Govezensky, T. ; Ventura, Cecilia Ileana Icon; Nuñez, Matias Icon; Bolcatto, Pablo Guillermo Icon; Barrio, R. A.

Otros responsables

Fecha

12/2022

Editorial

Nature

Revista

Scientific Reports

Título del libro

Nombre del evento

Fecha del evento

Institución organizadora

ISSN

2045-2322

eISSN

ISBN

Idioma

Inglés

Tipo del evento

Clasificación temática

Resumen

Many COVID-19 vaccines are proving to be highly effective to prevent severe disease and to diminish infections. Their uneven geographical distribution favors the appearance of new variants of concern, as the highly transmissible Delta variant, affecting particularly non-vaccinated people. It is important to device reliable models to analyze the spread of the different variants. A key factor is to consider the effects of vaccination as well as other measures used to contain the pandemic like social behaviour. The stochastic geographical model presented here, fulfills these requirements. It is based on an extended compartmental model that includes various strains and vaccination strategies, allowing to study the emergence and dynamics of the new COVID-19 variants. The model conveniently separates the parameters related to the disease from the ones related to social behavior and mobility restrictions. We applied the model to the United Kingdom by using available data to fit the recurrence of the currently prevalent variants. Our computer simulations allow to describe the appearance of periodic waves and the features that determine the prevalence of certain variants. They also provide useful predictions to help planning future vaccination boosters. We stress that the model could be applied to any other country of interest.

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Licencia Creative Commons

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