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Inferring age-specific differences in susceptibility to and infectiousness upon SARS-CoV-2 infection based on Belgian social contact data.

Nicolas FrancoPietro ColettiLander WillemLeonardo AngeliAdrien LajotSteven AbramsPhilippe BeutelsChristel FaesNiel Hens
Published in: PLoS computational biology (2022)
Several important aspects related to SARS-CoV-2 transmission are not well known due to a lack of appropriate data. However, mathematical and computational tools can be used to extract part of this information from the available data, like some hidden age-related characteristics. In this paper, we present a method to investigate age-specific differences in transmission parameters related to susceptibility to and infectiousness upon contracting SARS-CoV-2 infection. More specifically, we use panel-based social contact data from diary-based surveys conducted in Belgium combined with the next generation principle to infer the relative incidence and we compare this to real-life incidence data. Comparing these two allows for the estimation of age-specific transmission parameters. Our analysis implies the susceptibility in children to be around half of the susceptibility in adults, and even lower for very young children (preschooler). However, the probability of adults and the elderly to contract the infection is decreasing throughout the vaccination campaign, thereby modifying the picture over time.
Keyphrases
  • electronic health record
  • sars cov
  • big data
  • healthcare
  • risk factors
  • respiratory syndrome coronavirus
  • mental health
  • machine learning
  • young adults
  • oxidative stress
  • data analysis
  • coronavirus disease
  • deep learning