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SARS-CoV-2 seroprevalence among employees of a university hospital in Belgium during the 2020 COVID-19 outbreak (COVEMUZ-study)

Published online by Cambridge University Press:  05 July 2021

Deborah De Geyter*
Affiliation:
Clinical Biology, Laboratory of Microbiology and Infection Control, Universitair Ziekenhuis Brussel, Brussels, Belgium
Ellen Vancutsem
Affiliation:
Clinical Biology, Laboratory of Microbiology and Infection Control, Universitair Ziekenhuis Brussel, Brussels, Belgium
Sven Van Laere
Affiliation:
Biostatistics and Medical Informatics, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Belgium
Denis Piérard
Affiliation:
Clinical Biology, Laboratory of Microbiology and Infection Control, Universitair Ziekenhuis Brussel, Brussels, Belgium
Patrick Lacor
Affiliation:
Internal Medicine and Infectiology, Universitair Ziekenhuis Brussel, Brussels, Belgium
Ilse Weets
Affiliation:
Clinical Biology, Laboratory of Clinical Chemistry, Universitair Ziekenhuis Brussel, Brussels, Belgium
Sabine D. Allard
Affiliation:
Internal Medicine and Infectiology, Universitair Ziekenhuis Brussel, Brussels, Belgium
*
Author for correspondence: Deborah De Geyter, E-mail: Deborah.Degeyter@uzbrussel.be
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Abstract

Between 19 May and 12 June 2020, employees of the UZ Brussel were recruited in this study aiming to document the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence, to investigate the potential work-related risk factors for SARS-CoV-2 infection and to estimate the proportion of asymptomatic infections. In total, 2662 participants were included of whom 7.4% had immunoglobulin G antibodies against SARS-CoV-2. Of the participants reporting a positive polymerase chain reaction for SARS-CoV-2, 89% had antibodies at the time of blood sampling. Eleven per cent of the antibody positive participants reported no recent symptoms suggestive of coronavirus disease 2019 (COVID-19). Participants reporting fever, chest pain and/or anosmia/ageusia were significantly more frequently associated with the presence of antibodies against SARS-CoV-2. The presence of antibodies was highest in the group that had had contact with COVID-19-infected individuals outside the hospital with or without using appropriate personnel protective equipment (PPE) (P < 0.001). Inside the hospital, a statistically significant difference was observed for the employees considered as low-risk exposure compared to the intermediate-risk exposure group (P = 0.005) as well as the high-risk exposure group compared to the intermediate exposure risk group (P < 0.001). These findings highlight the importance of using correct PPE.

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Type
Original Paper
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press
Figure 0

Table 1. Characteristics of the employees of the UZ Brussels included in the study

Figure 1

Fig. 1. Overview of timing and seroprevalence of the study in comparison with COVID-19 epidemiology (number of cases and deaths) in Belgium. The study was performed between May 19th and June 12th 2020. Seropositive employees are shown in blue, seronegative ones in pink.

Figure 2

Fig. 2. Forest plot of bivariable models demonstrating the ORs with its 95% CI comparing the exposure variables in ascending order of risk to get infected with COVID-19.

Figure 3

Table 2. Presence or absence of SARS-CoV-2 IgG antibodies according to risk group and exposure to confirmed COVID-19 patients

Figure 4

Table 3. Logistic regression with seroprevalence as dependent variable and exposure risks (composed of their job function and answer of the respondent) as independent variable

Figure 5

Table 4. Definition of risk groups according to patient contact

Figure 6

Fig. 3. Forest plot of multivariate model with symptoms demonstrating the ORs with its 95% CI.

Figure 7

Table 5. Logistic regression with seroprevalence as dependent variable and symptoms questioned as independent variable