Severity of infection with the SARS-CoV-2 B.1.1.7 lineage among hospitalized COVID-19 patients in Belgium

Goethem, Nina Van; Vandromme, Mathil; Oyen, Herman Van; Haarhuis, Freek; Brondeel, Ruben; Catteau, Lucy; André, Emmanuel; Cuypers, Lize; Blot, Koen; Serrien, Ben

doi:10.1371/journal.pone.0269138

Cited by 6 publications

(7 citation statements)

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“…Van Goethem et al [ 30 ] compared COVID-19 disease severity between hospitalized patients in Belgium infected with the SARS-CoV-2 variant B.1.1.7 (Alpha) and those infected with previously circulating strains. Employing a causal framework, the authors observed no difference between patients infected with B.1.1.7 and those infected with older strains in terms of disease severity or in-hospital mortality.…”

Section: Studies Resulting From the Genomic Surveillance Initiativementioning

confidence: 99%

“…Employing a causal framework, the authors observed no difference between patients infected with B.1.1.7 and those infected with older strains in terms of disease severity or in-hospital mortality. However, Van Goethem et al [ 30 ] found that the estimated standardized risk of being admitted to an ICU was significantly higher when infected with the B.1.1.7 variant, and that among the younger age group (≤65 years), B.1.1.7 was significantly associated with both severe COVID-19 progression and ICU admission.…”

Section: Studies Resulting From the Genomic Surveillance Initiativementioning

confidence: 99%

“…Evolving towards a higher vaccination coverage (see Figure 6 ), post-vaccination breakthrough cases were asked to be sequenced only in particular situations, such as residents of long-term care facilities or when associated with increased disease severity. Along the road, it was requested that sequencing efforts be reinforced for the hospitalized population, mapping in detail the circulation of variants within hospitals and particular units in detail, allowing for association studies between different VOCs and disease severity ([ 30 , 31 ], but see also Section 4 ).…”

Section: Setting Up the National Genomic Surveillance Platform For Sa...mentioning

confidence: 99%

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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

Cuypers

Dellicour

Hong

et al. 2022

Viruses

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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.

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Section: Studies Resulting From the Genomic Surveillance Initiativementioning

confidence: 99%

Section: Studies Resulting From the Genomic Surveillance Initiativementioning

confidence: 99%

Section: Setting Up the National Genomic Surveillance Platform For Sa...mentioning

confidence: 99%

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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

Cuypers

Dellicour

Hong

et al. 2022

Viruses

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“…This sensitivity is especially important for the detection of emerging variants before they reach 1% of the circulating strains as was observed for the B.1.617.2 variant 2,24,41 . Also, the data gathered from the baseline genomic surveillance allowed the Belgian Sequencing Consortium to conduct or participate to several active surveillance studies concerning phylogenetic analyses, VOC‐associated disease severity assessments and outbreak investigations such as in nursing homes and others 26,49–54 …”

Section: Discussionmentioning

confidence: 99%

Genomic monitoring of SARS‐CoV‐2 variants using sentinel SARI hospital surveillance

Denayer,

Dufrasne,

Monsieurs

et al. 2023

Influenza Resp Viruses

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BackgroundTo support the COVID‐19 pandemic response, many countries, including Belgium, implemented baseline genomic surveillance (BGS) programs aiming to early detect and characterize new SARS‐CoV‐2 variants. In parallel, Belgium maintained a sentinel network of six hospitals that samples patients with severe acute respiratory infections (SARI) and integrated SARS‐CoV‐2 detection within a broader range of respiratory pathogens. We evaluate the ability of the SARI surveillance to monitor general trends and early signals of viral genetic evolution of SARS‐CoV‐2 and compare it with the BGS as a reference model.MethodsNine‐hundred twenty‐five SARS‐CoV‐2 positive samples from patients fulfilling the Belgian SARI definition between January 2020 and December 2022 were sequenced using the ARTIC Network amplicon tiling approach on a MinION platform. Weekly variant of concern (VOC) proportions and types were compared to those that were circulating between 2021 and 2022, using 96,251 sequences of the BGS.ResultsSARI surveillance allowed timely detection of the Omicron (BA.1, BA.2, BA.4, and BA.5) and Delta (B.1.617.2) VOCs, with no to 2 weeks delay according to the start of their epidemic growth in the Belgian population. First detection of VOCs B.1.351 and P.1 took longer, but these remained minor in Belgium. Omicron BA.3 was never detected in SARI surveillance. Timeliness could not be evaluated for B.1.1.7, being already major at the start of the study period.ConclusionsGenomic surveillance of SARS‐CoV‐2 using SARI sentinel surveillance has proven to accurately reflect VOCs detected in the population and provides a cost‐effective solution for long‐term genomic monitoring of circulating respiratory viruses.

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“…Additionally, hospital and ICU loads increase in epidemiological wave periods, with increased loads associated with increased disease severity and higher in-hospital mortality [107][108][109][110] of COVID-19 patients. Ideally, analyses should be adjusted for hospital load [111], ICU load [10,112] and COVID-19 incidence [111,113] to eliminate spurious association through these factors.…”

Section: Pressure On the Healthcare Systemmentioning

confidence: 99%

Evaluating methodological approaches to assess the severity of infection with SARS-CoV-2 variants: scoping review and applications on Belgian COVID-19 data

et al. 2022

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Background Differences in the genetic material of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants may result in altered virulence characteristics. Assessing the disease severity caused by newly emerging variants is essential to estimate their impact on public health. However, causally inferring the intrinsic severity of infection with variants using observational data is a challenging process on which guidance is still limited. We describe potential limitations and biases that researchers are confronted with and evaluate different methodological approaches to study the severity of infection with SARS-CoV-2 variants. Methods We reviewed the literature to identify limitations and potential biases in methods used to study the severity of infection with a particular variant. The impact of different methodological choices is illustrated by using real-world data of Belgian hospitalized COVID-19 patients. Results We observed different ways of defining coronavirus disease 2019 (COVID-19) disease severity (e.g., admission to the hospital or intensive care unit versus the occurrence of severe complications or death) and exposure to a variant (e.g., linkage of the sequencing or genotyping result with the patient data through a unique identifier versus categorization of patients based on time periods). Different potential selection biases (e.g., overcontrol bias, endogenous selection bias, sample truncation bias) and factors fluctuating over time (e.g., medical expertise and therapeutic strategies, vaccination coverage and natural immunity, pressure on the healthcare system, affected population groups) according to the successive waves of COVID-19, dominated by different variants, were identified. Using data of Belgian hospitalized COVID-19 patients, we were able to document (i) the robustness of the analyses when using different variant exposure ascertainment methods, (ii) indications of the presence of selection bias and (iii) how important confounding variables are fluctuating over time. Conclusions When estimating the unbiased marginal effect of SARS-CoV-2 variants on the severity of infection, different strategies can be used and different assumptions can be made, potentially leading to different conclusions. We propose four best practices to identify and reduce potential bias introduced by the study design, the data analysis approach, and the features of the underlying surveillance strategies and data infrastructure.

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Severity of infection with the SARS-CoV-2 B.1.1.7 lineage among hospitalized COVID-19 patients in Belgium

Cited by 6 publications

References 65 publications

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

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

Genomic monitoring of SARS‐CoV‐2 variants using sentinel SARI hospital surveillance

Evaluating methodological approaches to assess the severity of infection with SARS-CoV-2 variants: scoping review and applications on Belgian COVID-19 data

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