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Geenen C, Thibaut J, Laenen L, Raymenants J, Cuypers L, Maes P, Dellicour S, André E. Unravelling the effect of New Year's Eve celebrations on SARS-CoV-2 transmission. Sci Rep 2023; 13:22195. [PMID: 38097713 PMCID: PMC10721646 DOI: 10.1038/s41598-023-49678-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 12/11/2023] [Indexed: 12/17/2023] Open
Abstract
Public holidays have been associated with SARS-CoV-2 incidence surges, although a firm link remains to be established. This association is sometimes attributed to events where transmissions occur at a disproportionately high rate, known as superspreading events. Here, we describe a sudden surge in new cases with the Omicron BA.1 strain amongst higher education students in Belgium. Contact tracers classed most of these cases as likely or possibly infected on New Year's Eve, indicating a direct trigger by New Year celebrations. Using a combination of contact tracing and phylogenetic data, we show the limited role of superspreading events in this surge. Finally, the numerous simultaneous transmissions allowed a unique opportunity to determine the distribution of incubation periods of the Omicron strain. Overall, our results indicate that, even under social restrictions, a surge in transmissibility of SARS-CoV-2 can occur when holiday celebrations result in small social gatherings attended simultaneously and communitywide.
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Affiliation(s)
- Caspar Geenen
- Department of Microbiology, Immunology and Transplantation, Laboratory of Clinical Microbiology, KU Leuven, Herestraat 49, 3000, Leuven, Belgium.
| | - Jonathan Thibaut
- Department of Microbiology, Immunology and Transplantation, Laboratory of Clinical Microbiology, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Lies Laenen
- Department of Microbiology, Immunology and Transplantation, Laboratory of Clinical Microbiology, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
- Department of Laboratory Medicine, National Reference Centre for Respiratory Pathogens, University Hospitals Leuven, Leuven, Belgium
| | - Joren Raymenants
- Department of Microbiology, Immunology and Transplantation, Laboratory of Clinical Microbiology, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Lize Cuypers
- Department of Microbiology, Immunology and Transplantation, Laboratory of Clinical Microbiology, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
- Department of Laboratory Medicine, National Reference Centre for Respiratory Pathogens, University Hospitals Leuven, Leuven, Belgium
| | - Piet Maes
- Rega Institute, Department of Microbiology, Immunology and Transplantation, Laboratory of Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Simon Dellicour
- Rega Institute, Department of Microbiology, Immunology and Transplantation, Laboratory of Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
- Spatial Epidemiology Lab, Université Libre de Bruxelles, Brussels, Belgium
| | - Emmanuel André
- Department of Microbiology, Immunology and Transplantation, Laboratory of Clinical Microbiology, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
- Department of Laboratory Medicine, National Reference Centre for Respiratory Pathogens, University Hospitals Leuven, Leuven, Belgium
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Sobkowiak B, Haghmaram P, Prystajecky N, Zlosnik JEA, Tyson J, Hoang LMN, Colijn C. The utility of SARS-CoV-2 genomic data for informative clustering under different epidemiological scenarios and sampling. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2023; 113:105484. [PMID: 37531976 DOI: 10.1016/j.meegid.2023.105484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 07/25/2023] [Accepted: 07/30/2023] [Indexed: 08/04/2023]
Abstract
OBJECTIVES Clustering pathogen sequence data is a common practice in epidemiology to gain insights into the genetic diversity and evolutionary relationships among pathogens. We can find groups of cases with a shared transmission history and common origin, as well as identifying transmission hotspots. Motivated by the experience of clustering SARS-CoV-2 cases using whole genome sequence data during the COVID-19 pandemic to aid with public health investigation, we investigated how differences in epidemiology and sampling can influence the composition of clusters that are identified. METHODS We performed genomic clustering on simulated SARS-CoV-2 outbreaks produced with different transmission rates and levels of genomic diversity, along with varying the proportion of cases sampled. RESULTS In single outbreaks with a low transmission rate, decreasing the sampling fraction resulted in multiple, separate clusters being identified where intermediate cases in transmission chains are missed. Outbreaks simulated with a high transmission rate were more robust to changes in the sampling fraction and largely resulted in a single cluster that included all sampled outbreak cases. When considering multiple outbreaks in a sampled jurisdiction seeded by different introductions, low genomic diversity between introduced cases caused outbreaks to be merged into large clusters. If the transmission and sampling fraction, and diversity between introductions was low, a combination of the spurious break-up of outbreaks and the linking of closely related cases in different outbreaks resulted in clusters that may appear informative, but these did not reflect the true underlying population structure. Conversely, genomic clusters matched the true population structure when there was relatively high diversity between introductions and a high transmission rate. CONCLUSION Differences in epidemiology and sampling can impact our ability to identify genomic clusters that describe the underlying population structure. These findings can help to guide recommendations for the use of pathogen clustering in public health investigations.
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Affiliation(s)
| | - Pouya Haghmaram
- Department of Mathematics, Simon Fraser University, Burnaby, Canada
| | - Natalie Prystajecky
- BC Centre for Disease Control Public Health Laboratory, BC Centre for Disease Control, Vancouver, Canada; Department of Pathology and Laboratory Medicine, Faculty of Medicine, University of British Columbia, Canada
| | - James E A Zlosnik
- BC Centre for Disease Control Public Health Laboratory, BC Centre for Disease Control, Vancouver, Canada
| | - John Tyson
- BC Centre for Disease Control Public Health Laboratory, BC Centre for Disease Control, Vancouver, Canada
| | - Linda M N Hoang
- BC Centre for Disease Control Public Health Laboratory, BC Centre for Disease Control, Vancouver, Canada; Department of Pathology and Laboratory Medicine, Faculty of Medicine, University of British Columbia, Canada
| | - Caroline Colijn
- Department of Mathematics, Simon Fraser University, Burnaby, Canada
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