Belgium; COVID-19; RT-qPCR; SARS-CoV-2; nursing home; saliva test; worker; Immunology and Microbiology (all); Veterinary (all); General Veterinary; General Immunology and Microbiology; General Medicine
Abstract :
[en] Nursing home (NH) residents and staff have been severely affected by the COVID-19 pandemic. The aim of this study was to examine the use of weekly saliva RT-qPCR testing for SARS-CoV-2 detection among NH workers as a strategy to control disease transmission within NHs in Belgium. From 16 November to 27 December 2020, a voluntary and anonymous weekly screening was implemented in a cohort of 50,000 workers across 572 NHs in the Walloon region of Belgium to detect asymptomatic cases of SARS-CoV-2 via saliva RT-qPCR testing and using the Diagenode saliva sample collection device. Positive workers were isolated to avoid subsequent infections in residents and other staff. RT-qPCR testing was based on pooled saliva sampling techniques from three workers, followed by individual testing of each positive or inconclusive pool. The majority of NHs (85%) and 55% of their workers participated. Pooling did not affect sensitivity as it only induced a very decrease in sensitivity estimated as 0.33%. Significant decreases in the prevalence (34.4-13.4%) and incidence of NHs with either single (13.8-2%) or multiple positive workers (3.7-0%) were observed over time. In addition, deaths among NH residents and NH worker absences decreased significantly over time. Weekly saliva RT-qPCR testing for SARS-CoV-2 demonstrated large-scale feasibility and efficacy in disrupting the chain of transmission. Implementation of this testing strategy in NHs could also be extended to other settings with the aim to control viral transmission for maintaining essential activities.
Disciplines :
Immunology & infectious disease
Author, co-author :
Saegerman, Claude ; Université de Liège - ULiège > Fundamental and Applied Research for Animals and Health (FARAH) > FARAH: Santé publique vétérinaire
Donneau, Anne-Françoise ; Université de Liège - ULiège > Santé publique : de la Biostatistique à la Promotion de la Santé
Speybroeck, Niko ; Research Institute of Health and Society, Catholic University of Louvain, Brussels, Belgium
Diep, Anh Nguyet ; Biostatistics Unit, Liège University, Liège, Belgium
Williams, Alexandria; P95 Pharmacovigilance and Epidemiology, Leuven, Belgium
Stamatakis, Lambert; General Delegation COVID-19, Government of the Walloon Region, Namur, Belgium
Coppieters, Wouter ; Université de Liège - ULiège > Département de gestion vétérinaire des Ressources Animales (DRA) > Génomique animale
Michel, Fabienne ; Université de Liège - ULiège > Département d'économie > UER Economie : Economie sociale et systèmes économiques
Breuer, Christophe ; Université de Liège - ULiège > Département de géographie
Dandoy, Margaux ; Université de Liège - ULiège > HEC Liège : UER > UER Opérations : Recherche opérationnelle et gestion de la production
Ek, Olivier ; Université de Liège - ULiège > GIGA > GIGA I3 - Cellular and Molecular Immunology
Gourzonès, Claire ; Université de Liège - ULiège > GIGA > GIGA I3 - Cellular and Molecular Immunology
Schyns, Joey ; Université de Liège - ULiège > GIGA > GIGA I3 - Cellular and Molecular Immunology
Goffin, Emeline ; Université de Liège - ULiège > GIGA > GIGA I3 - Cellular and Molecular Immunology
Minner, Frédéric ; Université de Liège - ULiège > GIGA > GIGA I3 - Cellular and Molecular Immunology
Renault, Véronique ; Université de Liège - ULiège > Fundamental and Applied Research for Animals and Health (FARAH) > FARAH: Santé publique vétérinaire
Gillet, Laurent ✱; Université de Liège - ULiège > Fundamental and Applied Research for Animals and Health (FARAH) > FARAH: Santé publique vétérinaire
Bureau, Fabrice ✱; Université de Liège - ULiège > Département des sciences fonctionnelles (DSF) > Biochimie et biologie moléculaire
We gratefully acknowledge the Government of Wallonia for their financial support within the framework of a public contract initiated by the Walloon Agency for a Quality Life (AViQ), as well as Liège University for their collaboration in the project. This work would not have been accomplished without the engagement of participating NHs and people involved in the University of Liège Covid‐19 Platform, in particular E. Baudri, W. Berriche, B. Boniver, J. Fonzé, H. Gillet, S. Guilliams, J. Noël, T. Nothomb, M. Pathammavong, J. Patiny, L. Robaye, J. Smeets, D. Tonneau, Z. Truffaut, T. Weigert. Therefore, we thank them for their dedicated time and trust. Raw data used to generate Figure 3 were provided by Sciensano, the Belgian Institute for Health.
Coronaviridae Study Group of the International Committee on Taxonomy of Viruses. The species severe acute respiratory syndrome-related coronavirus: Classifying 2019-nCoV and naming it SARS-CoV-2. (2020). Nature Microbiology, 5, 536–544. https://doi.org/10.1038/s41564-020-0695-z
Czumbel, L. M., Kiss, S., Farkas, N., Mandel, I., Hegyi, A., Nagy, Á., Lohinai, Z., Szakács, Z., Hegyi, P., Steward, M. C., & Varga, G. (2020). Saliva as a candidate for COVID-19 diagnostic testing: a meta-analysis. Frontiers in Medicine, 7, 465. https://doi.org/10.3389/fmed.2020.00465
Eberhardt, J. N., Breuckmann, N. P., & Eberhardt, C. S. (2020). Challenges and issues of SARS-CoV-2 pool testing. The Lancet Infectious Diseases, 20(11), 1233–1234. https://doi.org/10.1016/S1473-3099(20)30467-9
Fakheran, O., Dehghannejad, M., & Khademi, A. (2020). Saliva as a diagnostic specimen for detection of SARS-CoV-2 in suspected patients: a scoping review. Infectious Diseases of Poverty, 9(1), 100. https://doi.org/10.1186/s40249-020-00728-w
Fox, J., & Weisberg, S. (2018). An R Companion to Applied Regression. third edition. Sage, Thousand Oaks, CA
Garcia-Beltran, W. F., Lam, E. C., St Denis, K., Nitido, A. D., Garcia, Z. H., Hauser, B. M., Feldman, J., Pavlovic, M. N., Gregory, D. J., Poznansky, M. C., Sigal, A., Schmidt, A. G., Iafrate, A. J., Naranbhai, V., & Balazs, A. B. (2021). Multiple SARS-CoV-2 variants escape neutralization by vaccine-induced humoral immunity. Cell, 184(9), 2372–2383.e9. https://doi.org/10.1016/j.cell.2021.03.013
Harvey, W. T., Carabelli, A. M., Jackson, B., Gupta, R. K., Thomson, E. C., Harrison, E. M., Ludden, C., Reeve, R., Rambaut, A., COVID-19 Genomics UK (COG-UK) Consortium, Peacock, S. J., & Robertson, D. L. (2021). SARS-CoV-2 variants, spike mutations and immune escape. Nature Reviews Microbiology, 1–16. https://doi.org/10.1038/s41579-021-00573-0
Heinze, G., & Schemper, M. (2002). A solution to the problem of separation in logistic regression. Statistics in Medicine, 21, 2409–2419.
Li, Y., Li, K., Xiong, W., Wang, X., Liu, C., Liu, C., Tan, W., Luo, B., Zhu, Y., Wu, Y., Yin, H., Li, X., & Li, Z. (2020). Clinical characteristics and viral shedding kinetics of 38 asymptomatic patients with coronavirus disease 2019: A retrospective observational study. Medicine, 99(51), e23547. https://doi.org/10.1097/MD.0000000000023547
Lohse, S., Pfuhl, T., Berkó-Göttel, B., Rissland, J., Geißler, T., Gärtner, B., Becker, S. L., Schneitler, S., & Smola, S. (2020). Pooling of samples for testing for SARS-CoV-2 in asymptomatic people. The Lancet Infectious Diseases, 20(11), 1231–1232. https://doi.org/10.1016/S1473-3099(20)30362-5
Petrie, A., & Watson, P. (2013). Statistics for veterinary and animal science. This edition, John Wiley & Sons, Ltd, West Sussex, UK, 391.
Preux, P. M., Odermatt, P., Perna, A., Marin, B., & Vergnenégre, A. (2005). Qu'est-ce qu'une régression logistique ? Revue Des Maladies Respiratoires, 22, 159–162.
QGIS Development Team. (2020). QGIS Geographic Information System. Open-Source Geospatial Foundation, URL http://qgis.org
R Core Team. (2013). R: A language and environment for statistical computer. R Foundation for Statistical Computing, Vienna, Austria, https://www.r-project.org
Saegerman, C., Gilbert, A., Donneau, A. -. F., Gangolf, M., Nguvet Diep, A., Meix, C., Bontems, S., Hayette, M. -. P., D'Orio, V., & Ghuysen, A. (2021). Clinical decision support tool for diagnosis of COVID-19 in hospitals. PLoS One, 6(3), e0247773. https://doi.org/10.1371/journal.pone.0247773
Sciensano. (2020) Définition de cas, indications de demande d'un test et déclaration obligatoire de cas COVID-19. Version du 31 décembre 2020. Sciensano, Bruxelles, Belgium, https://covid-19.sciensano.be/sites/default/files/Covid19/COVID-19_Case%20definition_Testing_FR.pdf
Sciensano. (2021b) Surveillance en maisons de repos et maisons de repos et de soins. Rapport de la semaine 52 (données jusqu'au 5 janvier 2021 inclus). Sciensano, Bruxelles, Belgique. https://covid-19.sciensano.be/sites/default/files/Covid19/COVID-19_Surveillance_MR_MRS.pdf
StataCorp. (2015). Stata Statistical Software: Release 14. College Station, TX: StataCorp LP, USA.
World Health Organization. (2021) WHO Coronavirus (COVID-19) Dashboard. https://covid19.who.int/ (accessed May 2, 2021).
Wyllie, A. L., Fournier, J., Casanovas-Massana, A., Campbell, M., Tokuyama, M., Vijayakumar, P., Warren, J. L., Geng, B., Muenker, M. C., Moore, A. J., Vogels, C. B. F., Petrone, A. E., Ott, I. M., Lu, P., Venkataraman, A., Lu-Culligan, A., Klein, J., Earnest, R., Simonov, M., … Ko, A. I. (2020). Saliva or Nasopharyngeal Swab Specimens for Detection of SARS-CoV-2. New England Journal of Medicine, 383(13):1283–1286. https://doi.org/10.1056/NEJMc2016359
