Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/36884
Title: The COVID-19 wave in Belgium during the Fall of 2020 and its association with higher education
Authors: NATALIA, Yessika 
FAES, Christel 
NEYENS, Thomas 
MOLENBERGHS, Geert 
Editors: Săndulescu, Oana
Issue Date: 2022
Publisher: 
Source: PLoS One, 17 (2) (Art N° e0264516)
Abstract: Soon after SARS-CoV-2 emerged in late 2019, Belgium was confronted with a first COVID-19 wave in March-April 2020. SARS-CoV-2 circulation declined in the summer months (late May to early July 2020). Following a successfully trumped late July-August peak, COVID-19 incidence fell slightly, to then enter two successive phases of rapid incline: in the first half of September, and then again in October 2020. The first of these coincided with the peak period of returning summer travelers; the second one coincided with the start of higher education's academic year. The largest observed COVID-19 incidence occurred in the period 16-31 October, particularly in the Walloon Region, the southern, French-speaking part of Belgium. We examine the potential association of the higher education population with spatio-temporal spread of COVID-19, using Bayesian spatial Poisson models for confirmed test cases, accounting for socio-demographic heterogeneity in the population. We find a significant association between the number of COVID-19 cases in the age groups 18-29 years and 30-39 years and the size of the higher education student population at the municipality level. These results can be useful towards COVID-19 mitigation strategies, particularly in areas where virus transmission from higher education students into the broader community could exacerbate morbidity and mortality of COVID-19 among populations with prevalent underlying conditions associated with more severe outcomes following infection.
Document URI: http://hdl.handle.net/1942/36884
ISSN: 1932-6203
e-ISSN: 1932-6203
DOI: 10.1371/journal.pone.0264516
ISI #: 000787811000113
Rights: Copyright: © 2022 Natalia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Category: A1
Type: Journal Contribution
Validations: ecoom 2023
Appears in Collections:Research publications

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