MOOD publications

@article{@article{2022b,

title = {Two Years of Genomic Surveillance in Belgium during the SARS-CoV-2 Pandemic to Attain Country-Wide Coverage and Monitor the Introduction and Spread of Emerging Variants},

author = {Cuypers, Lize and Dellicour, Simon and Hong, Samuel L. and Potter, Barney I. and Verhasselt, Bruno and Vereecke, Nick and Lambrechts, Laurens and Durkin, Keith and Bours, Vincent and Klamer, Sofieke and Bayon-Vicente, Guillaume and Vael, Carl and Ariën, Kevin K. and De Mendonca, Ricardo and Soetens, Oriane and Michel, Charlotte and Bearzatto, Bertrand and Naesens, Reinout and Gras, Jeremie and Vankeerberghen, Anne and Matheeussen, Veerle and Martens, Geert and Obbels, Dagmar and Lemmens, Ann and Van den Poel, Bea and Van Even, Ellen and De Rauw, Klara and Waumans, Luc and Reynders, Marijke and Degosserie, Jonathan and Maes, Piet and André, Emmanuel and Baele, Guy},

url = {https://www.mdpi.com/1999-4915/14/10/2301},

doi = {https://doi.org/10.3390/v14102301},

issn = {1999-4915},

year  = {2022},

date = {2022-10-20},

urldate = {2022-10-20},

journal = {Viruses},

volume = {14},

number = {10},

pages = {2301},

abstract = {An adequate SARS-CoV-2 genomic surveillance strategy has proven to be essential for countries to obtain a thorough understanding of the variants and lineages being imported and successfully established within their borders. During 2020, genomic surveillance in Belgium was not structurally implemented but performed by individual research laboratories that had to acquire the necessary funds themselves to perform this important task. At the start of 2021, a nationwide genomic surveillance consortium was established in Belgium to markedly increase the country’s genomic sequencing efforts (both in terms of intensity and representativeness), to perform quality control among participating laboratories, and to enable coordination and collaboration of research projects and publications. We here discuss the genomic surveillance efforts in Belgium before and after the establishment of its genomic sequencing consortium, provide an overview of the specifics of the consortium, and explore more details regarding the scientific studies that have been published as a result of the increased number of Belgian SARS-CoV-2 genomes that have become available.},

keywords = {Belgium, COVID-19, genomic surveillance, next-generation sequencing, SARS-CoV-2, variants of concern},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Investigating the drivers of the spatio-temporal heterogeneity in COVID-19 hospital incidence—Belgium as a study case},

author = {Simon Dellicour, Catherine Linard, Nina Van Goethem, Daniele Da Re, Jean Artois, Jérémie Bihin, Pierre Schaus, François Massonnet, Herman Van Oyen, Sophie O. Vanwambeke, Niko Speybroeck, Marius Gilbert },

url = {https://ij-healthgeographics.biomedcentral.com/articles/10.1186/s12942-021-00281-1},

doi = {https://doi.org/10.1186/s12942-021-00281-1},

issn = {1476-072X},

year  = {2021},

date = {2021-06-14},

urldate = {2021-06-14},

journal = {International Journal of Health Geographics},

number = {29},

issue = {20},

abstract = {Background

The COVID-19 pandemic is affecting nations globally, but with an impact exhibiting significant spatial and temporal variation at the sub-national level. Identifying and disentangling the drivers of resulting hospitalisation incidence at the local scale is key to predict, mitigate and manage epidemic surges, but also to develop targeted measures. However, this type of analysis is often not possible because of the lack of spatially-explicit health data and spatial uncertainties associated with infection.



Methods

To overcome these limitations, we propose an analytical framework to investigate potential drivers of the spatio–temporal heterogeneity in COVID-19 hospitalisation incidence when data are only available at the hospital level. Specifically, the approach is based on the delimitation of hospital catchment areas, which allows analysing associations between hospitalisation incidence and spatial or temporal covariates. We illustrate and apply our analytical framework to Belgium, a country heavily impacted by two COVID-19 epidemic waves in 2020, both in terms of mortality and hospitalisation incidence.



Results

Our spatial analyses reveal an association between the hospitalisation incidence and the local density of nursing home residents, which confirms the important impact of COVID-19 in elderly communities of Belgium. Our temporal analyses further indicate a pronounced seasonality in hospitalisation incidence associated with the seasonality of weather variables. Taking advantage of these associations, we discuss the feasibility of predictive models based on machine learning to predict future hospitalisation incidence.



Conclusion

Our reproducible analytical workflow allows performing spatially-explicit analyses of data aggregated at the hospital level and can be used to explore potential drivers and dynamic of COVID-19 hospitalisation incidence at regional or national scales.},

keywords = {Belgium, Boosted regression trees, COVID-19, Hospitalisation incidence, Spatial covariates, Temporal covariates},

pubstate = {published},

tppubtype = {article}

}

@article{ingelbeen2021reducing,

title = {Reducing contacts to stop SARS-CoV-2 transmission during the second pandemic wave in Brussels, Belgium, August to November 2020},

author = {Brecht Ingelbeen and Laur`ene Peckeu and Marie Laga and Ilona Hendrix and Inge Neven and Marianne AB Sande and Esther Kleef},

doi = {https://doi.org/10.1371/journal.pbio.3001115},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Eurosurveillance},

volume = {26},

number = {7},

pages = {2100065},

publisher = {European Centre for Disease Prevention and Control},

abstract = {To evaluate the effect of physical distancing and school reopening in Brussels between August and November 2020, we monitored changes in the number of reported contacts per SARS-CoV-2 case and associated SARS-CoV-2 transmission. The second COVID-19 pandemic wave in Brussels was the result of increased social contact across all ages following school reopening. Physical distancing measures including closure of bars and restaurants, and limiting close contacts, while primary and secondary schools remained open, reduced social mixing and controlled SARS-CoV-2 transmission.},

keywords = {Belgium, COVID-19, epidemiology, Model, school, transmission},

pubstate = {published},

tppubtype = {article}

}