Predicting COVID-19 pandemic waves including vaccination data with deep learning.

Journal: Frontiers in public health
PMID: 38162619

Abstract

INTRODUCTION: During the recent COVID-19 pandemics, many models were developed to predict the number of new infections. After almost a year, models had also the challenge to include information about the waning effect of vaccines and by infection, and also how this effect start to disappear.

Authors

  • Ahmed Begga
    Instituto Universitario de Matemática Pura y Aplicada, Universitat Politécnica de València, València, Spain.
  • Òscar Garibo-I-Orts
    Instituto Universitario de Matemática Pura y Aplicada, Universitat Politécnica de València, València, Spain.
  • Sergi de María-García
    Instituto Universitario de Matemática Pura y Aplicada, Universitat Politécnica de València, València, Spain.
  • Francisco Escolano
    Departamento de Ciencia de la Computación e I.A., Universidad de Alicante, Alicante, Spain.
  • Miguel A Lozano
    Departamento de Ciencia de la Computación e I.A., Universidad de Alicante, Alicante, Spain.
  • Nuria Oliver
  • J Alberto Conejero
    Instituto Universitario de Matemática Pura y Aplicada, Universitat Politécnica de Valéncia, Camino de Vera s/n, Valencia 46022, Spain. Electronic address: aconejero@upv.es.

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