Public Health, Environmental and Occupational Health
Abstract :
[en] Background
The role played by large-scale repetitive SARS-CoV-2 screening programs within university populations interacting continuously with an urban environment, is unknown. Our objective was to develop a model capable of predicting the dispersion of viral contamination among university populations dividing their time between social and academic environments.
Methods
Data was collected through real, large-scale testing developed at the University of Liège, Belgium, during the period Sept. 28th-Oct. 29th 2020. The screening, offered to students and staff (n = 30,000), began 2 weeks after the re-opening of the campus but had to be halted after 5 weeks due to an imposed general lockdown. The data was then used to feed a two-population model (University + surrounding environment) implementing a generalized susceptible-exposed-infected-removed compartmental modeling framework.
Results
The considered two-population model was sufficiently versatile to capture the known dynamics of the pandemic. The reproduction number was estimated to be significantly larger on campus than in the urban population, with a net difference of 0.5 in the most severe conditions. The low adhesion rate for screening (22.6% on average) and the large reproduction number meant the pandemic could not be contained. However, the weekly screening could have prevented 1393 cases (i.e. 4.6% of the university population; 95% CI: 4.4–4.8%) compared to a modeled situation without testing.
Conclusion
In a real life setting in a University campus, periodic screening could contribute to limiting the SARS-CoV-2 pandemic cycle but is highly dependent on its environment.
Disciplines :
Immunology & infectious disease
Author, co-author :
Denoël, Vincent ✱; Université de Liège - ULiège > Urban and Environmental Engineering
Bruyère, Olivier ✱; Centre Hospitalier Universitaire de Liège - CHU > > Service de médecine de l'appareil locomoteur
Louppe, Gilles ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Big Data
D'ORIO, Vincenzo ; Université de Liège - ULiège > Département des sciences cliniques
Fontaine, Sébastien ; Université de Liège - ULiège > Institut de recherche en Sciences Sociales (IRSS) > IRSS: Centre d'Etude de l'Opinion de l'Université de Liège (CLEO)
Gillet, Laurent ; Université de Liège - ULiège > Fundamental and Applied Research for Animals and Health (FARAH) > FARAH: Santé publique vétérinaire
Guillaume, Michèle ; Université de Liège - ULiège > Santé publique : de la Biostatistique à la Promotion de la Santé
Haubruge, Eric ; Université de Liège - ULiège > GxABT : Services généraux du site > Site GxABT - Cabinet du Vice-recteur
Lange, Anne-Catherine ; Université de Liège - ULiège > Département de mathématique > Probabilités et statistique mathématique
Michel, Fabienne ; Université de Liège - ULiège > Département d'économie > UER Economie : Economie sociale et systèmes économiques
Hulle, Romain Van
Arnst, Maarten ; Université de Liège - ULiège > Aérospatiale et Mécanique (A&M)
Donneau, Anne-Françoise ✱; Université de Liège - ULiège > Santé publique : de la Biostatistique à la Promotion de la Santé
Saegerman, Claude ✱; Université de Liège - ULiège > Fundamental and Applied Research for Animals and Health (FARAH) > FARAH: Santé publique vétérinaire
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