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Artículo

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

Barreiro, Nadia Luisina; Govezensky, T.; Ventura, Cecilia IleanaIcon ; Nuñez, MatiasIcon ; Bolcatto, Pablo GuillermoIcon ; Barrio, R. A.
Fecha de publicación: 12/2022
Editorial: Nature
Revista: Scientific Reports
ISSN: 2045-2322
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Epidemiología

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.
Palabras clave: COVID-19 , Vaccines , Strains , United Kingdom
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info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution 2.5 Unported (CC BY 2.5)
Identificadores
URI: http://hdl.handle.net/11336/202320
DOI: http://dx.doi.org/10.1038/s41598-022-16147-w
Colecciones
Articulos(CCT - PATAGONIA NORTE)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - PATAGONIA NORTE
Articulos(IMAL)
Articulos de INST.DE MATEMATICA APLICADA "LITORAL"
Articulos(INIBIOMA)
Articulos de INST. DE INVEST.EN BIODIVERSIDAD Y MEDIOAMBIENTE
Citación
Barreiro, Nadia Luisina; Govezensky, T.; Ventura, Cecilia Ileana; Nuñez, Matias; Bolcatto, Pablo Guillermo; et al.; Modelling the interplay of SARS-CoV-2 variants in the United Kingdom; Nature; Scientific Reports; 12; 1; 12-2022; 1-8
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