Reconstruction of SARS-CoV-2 outbreaks in a primary school using epidemiological and genomic data
Cécile Kremer,
Andrea Torneri,
Pieter J.K. Libin,
Cécile Meex,
Marie-Pierre Hayette,
Sébastien Bontems,
Keith Durkin,
Maria Artesi,
Vincent Bours,
Philippe Lemey,
Gilles Darcis,
Niel Hens,
Christelle Meuris
Affiliations
Cécile Kremer
Interuniversity Institute for Biostatistics and statistical Bioinformatics, Data Science Institute, Hasselt University, Hasselt, Belgium; Correspondence to: Agoralaan Gebouw D, 3590 Diepenbeek, Belgium.
Andrea Torneri
Interuniversity Institute for Biostatistics and statistical Bioinformatics, Data Science Institute, Hasselt University, Hasselt, Belgium
Pieter J.K. Libin
Interuniversity Institute for Biostatistics and statistical Bioinformatics, Data Science Institute, Hasselt University, Hasselt, Belgium; Artificial Intelligence Lab, Department of Computer Science, Vrije Universiteit Brussel, Brussels, Belgium; Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, University of Leuven, Leuven, Belgium
Cécile Meex
Department of Clinical Microbiology, University of Liège, Liège, Belgium
Marie-Pierre Hayette
Department of Clinical Microbiology, University of Liège, Liège, Belgium
Sébastien Bontems
Department of Clinical Microbiology, University of Liège, Liège, Belgium
Keith Durkin
Laboratory of Human Genetics, GIGA-Institute, University of Liège, Liège, Belgium
Maria Artesi
Laboratory of Human Genetics, GIGA-Institute, University of Liège, Liège, Belgium
Vincent Bours
Laboratory of Human Genetics, GIGA-Institute, University of Liège, Liège, Belgium
Philippe Lemey
Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, University of Leuven, Leuven, Belgium
Gilles Darcis
Department of Infectious Diseases, Liège University Hospital, Liège, Belgium
Niel Hens
Interuniversity Institute for Biostatistics and statistical Bioinformatics, Data Science Institute, Hasselt University, Hasselt, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
Christelle Meuris
Department of Infectious Diseases, Liège University Hospital, Liège, Belgium
Mathematical modelling studies have shown that repetitive screening can be used to mitigate SARS-CoV-2 transmission in primary schools while keeping schools open. However, not much is known about how transmission progresses within schools and whether there is a risk of importation to households. During the academic year 2020–2021, a prospective surveillance study using repetitive screening was conducted in a primary school and associated households in Liège (Belgium). SARS-CoV-2 screening was performed via throat washing either once or twice a week. We used genomic and epidemiological data to reconstruct the observed school outbreaks using two different models. The outbreaker2 model combines information on the generation time and contact patterns with a model of sequence evolution. For comparison we also used SCOTTI, a phylogenetic model based on the structured coalescent. In addition, we performed a simulation study to investigate how the accuracy of estimated positivity rates in a school depends on the proportion of a school that is sampled in a repetitive screening strategy. We found no difference in SARS-CoV-2 positivity between children and adults and children were not more often asymptomatic compared to adults. Both models for outbreak reconstruction revealed that transmission occurred mainly within the school environment. Uncertainty in outbreak reconstruction was lowest when including genomic as well as epidemiological data. We found that observed weekly positivity rates are a good approximation to the true weekly positivity rate, especially in children, even when only 25% of the school population is sampled. These results indicate that, in addition to reducing infections as shown in modelling studies, repetitive screening in school settings can lead to a better understanding of the extent of transmission in schools during a pandemic and importation risk at the community level.
