Your browser doesn't support javascript.
loading
Minimizing school disruption under high incidence conditions due to the Omicron variant in early 2022
Elisabetta Colosi; Giulia Bassignana; Alain Barrat; Bruno Lina; Philippe Vanhems; Julia Bielicki; Vittoria Colizza.
Affiliation
  • Elisabetta Colosi; INSERM, Sorbonne Université, Pierre Louis Institute of Epidemiology and Public Health, Paris, France
  • Giulia Bassignana; INSERM, Sorbonne Université, Pierre Louis Institute of Epidemiology and Public Health, Paris, France
  • Alain Barrat; Aix Marseille Univ, Université de Toulon, CNRS, CPT, Turing Center for Living Systems, Marseille, France
  • Bruno Lina; National Reference Center for Respiratory Viruses, Department of Virology, Infective Agents Institute, Croix-Rousse Hospital, Hospices Civils de Lyon, Lyon, Fra
  • Philippe Vanhems; Service d'Hygiène, Épidémiologie, Infectiovigilance et Prévention, Hospices Civils de Lyon, Lyon, France
  • Julia Bielicki; Paediatric Infectious Diseases, University of Basel Children's Hospital, Spitalstrasse 33, 4056, Basel, Switzerland
  • Vittoria Colizza; INSERM, Sorbonne Université, Pierre Louis Institute of Epidemiology and Public Health, Paris, France
Preprint in En | PREPRINT-MEDRXIV | ID: ppmedrxiv-22270473
ABSTRACT
As record cases due to the Omicron variant are currently registered in Europe, schools remain a vulnerable setting suffering large disruption. Extending previous modeling of SARS-CoV-2 transmission in schools in France, we estimate that at high incidence rates reactive screening protocols (as currently applied in France) require comparable test resources as weekly screening (as currently applied in some Swiss cantons), for considerably lower control. Our findings can be used to define incidence levels triggering school protocols and optimizing their cost-effectiveness.
License
cc_by_nd
Full text: 1 Collection: 09-preprints Database: PREPRINT-MEDRXIV Type of study: Observational_studies Language: En Year: 2022 Document type: Preprint
Full text: 1 Collection: 09-preprints Database: PREPRINT-MEDRXIV Type of study: Observational_studies Language: En Year: 2022 Document type: Preprint