Increased household transmission and immune escape of the SARS-CoV-2 Omicron variant compared to the Delta variant: evidence from Norwegian contact tracing and vaccination data

Jalali, Neda; Brustad, Hilde K.; Frigessi, Arnoldo; MacDonald, Emily; Meijerink, Hinta; Feruglio, Siri Laura; Nygård, Karin; Rø, Gunnar; Madslien, Elisabeth Henie; Blasio, Birgitte Freiesleben de

doi:10.21203/rs.3.rs-1370541/v1

Cited by 18 publications

(37 citation statements)

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“…We identified 2097 records (1791 from PubMed, 306 from medRxiv, and 2 from reference lists of eligible articles) published between June 18, 2021, and March 8, 2022 (eFigure 1 in the Supplement ). Fifty-eight new studies 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 (eTable 2 in the Supplement ) were combined with 77 studies from ou...…”

Section: Resultsmentioning

confidence: 99%

“…This reflects new variants and changing vaccination coverage. From highest to lowest, the overall household SARs were 42.7% (95% CI, 35.4%-50.4%) for Omicron (7 studies 55 , 61 , 62 , 63 , 64 , 67 , 68 ), 36.4% (95% CI, 33.4%-39.5%) for Alpha (11 studies 18 , 19 , 21 , 23 , 28 , 33 , 44 , 46 , 49 , 50 , 69 ), 29.7% (95% CI, 23.0%-37.3%) for Delta (16 studies 18 , 20 , 24 , 26 , 35 , 37 , 42 , 46 , 50 , 55 , 57 , 61 , 64 , 65 , 66 , 70 ), and 22.5% (95% CI, 18.6%-26.8%) for Beta (3 studies 15 , 18 , 50 ) ( Figure 2 ). High heterogeneity was found among studies for Omicron ( I 2 = 98.2%; P < .001) and Delta ( I 2 = 99.1%; P < .001), moderate for Alpha ( I 2 = 59.6%; P < .001), and low for Beta ( I 2 = 2.6%; P = .79).…”

Section: Resultsmentioning

confidence: 99%

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Household Secondary Attack Rates of SARS-CoV-2 by Variant and Vaccination Status

et al. 2022

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Household Secondary Attack Rates of SARS-CoV-2 by Variant and Vaccination Status

et al. 2022

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“…Omicron is generally understood to have a transmission advantage but is less pathogenic than Delta, 16,17,36,37 however quantifying and thus comparing these parameters is difficult given differences in the populations in which they are circulating, and availability and access to early characterising data. While Omicron infections are dominating Delta infections in most parts of the world, its reproduction advantage may be due to increased inherent transmissibility, increased immunity escape, a different population response to arrival of Omicron, or some combination of these.…”

Section: Managing the Health Burdenmentioning

confidence: 99%

“…While Omicron infections are dominating Delta infections in most parts of the world, its reproduction advantage may be due to increased inherent transmissibility, increased immunity escape, a different population response to arrival of Omicron, or some combination of these. 37 To manage this uncertainty, we employed the calibration process described in the methods section. This exploited the availability of detailed Omicron epidemic data from two Australian states, Queensland and South Australia.…”

Section: Managing the Health Burdenmentioning

confidence: 99%

SARS-CoV-2 Omicron disease burden in Australia following border reopening: a modelling analysis

Milne

Carrivick

2022

Preprint

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Background: Countries with high COVID-19 vaccination rates have seen the SARS-CoV-2 Omicron variant result in rapidly increasing case numbers. This study evaluated the impact on the health system which may occur following introduction of the Omicron variant into Western Australia following state border reopening. We aimed to understand the effect of high vaccine coverage levels on the population health burden in the context of lower vaccine effectiveness against the Omicron variant, the impact of a third dose booster regime, and ongoing waning of vaccine-induced immunity. Originally scheduled for 5th February 2022, the Western Australian border was opened on 3rd March 2022, we also aimed to determine the impact of delaying border reopening on the COVID-19 health burden and whether the West Australian health system would be able to manage the resulting peak demand. Methods: An agent-based model was used to evaluate changes in the COVID-19 health burden resulting from different border openings, at monthly intervals. We assumed immunity was derived from vaccination with the BNT162b2 Pfizer BioNTech vaccine and waned at observed rates taken from the UK. The model was calibrated against outbreaks in two other Australian states, Queensland and South Australia, both of which were in a similar situation to Western Australia with negligible COVID-19 transmission prior to Omicron variant introduction. Age-specific infections generated by the model, together with recent UK data, permitted resulting outbreak health burden to be quantified, in particular peak ICU demand. Results: Overall population immunity in Western Australia is shown to peak and then plateau for a period of 5 months, between February and June 2022, resulting in a similar health burden if the border is reopened prior to June 2022. For an opening date of 5th March 2022, hospitalisations are predicated to peak at 510 beds, 51 of which will be in ICU, with a total of 383 deaths. If the border reopened on 5th June 2022, hospitalisations are expected to peak with 750 beds required, 75 of which would be in ICU, and a total of 478 deaths. With a total surge capacity of 52 fully staffed ICU beds, West Australian hospitals are predicted to have adequate ICU capacity for future COVID-19 demands if border reopening occurs prior to May 2022. Conclusions: Our results show that with extremely high SARS-CoV-2 vaccination rates in Western Australian, and documented vaccine-induced vaccine waning rates, the overall population immunity in Western Australia will be at its highest in the period of February 2022 to June 2022. Opening the Western Australian border prior to the end this period will result in the lowest health burden in comparison to opening in June 2022 or later. With a border reopening of 3rd March 2022 announced by the Western Australian government, our data for a 5th March 2022 opening date may be used to predict the progression of this resulting outbreak. These data show expected peak demand of 510 hospital beds, 51 of which will be in ICU, with a total of 383 deaths. With a surge capacity of 52 ICU beds, it is expected that the Western Australian hospital system will be able to handle the additional load during the peak of the wave.

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“…3 The immune escape capabilities are possibly conferred by K417N, 37 S477N, 38 E484A 38 and other novel mutations, while the binding affinity between RBD and hACE2 is retained due to strongly binding-improving mutations such as N501Y, 30,31 both contributing to the increased viral transmissibility of Omicron compared to earlier variants. [39][40][41] Early on during the pandemic, to gain a more complete view of the effect of RBD mutation, Starr et al 30 exhaustively assessed the impact of single amino acid changes on RBD expression and hACE2 binding. They found that 84.5% of the amino acid changes are detrimental, 7.5% are neutral and the rest 8.0% can lead to enhanced binding of the RBD with hACE2.…”

Section: Introductionmentioning

confidence: 99%

A CNN model for predicting binding affinity changes between SARS-CoV-2 spike RBD variants and ACE2 homologues

Chen¹,

Boorla²,

Chowdhury³

et al. 2022

Preprint

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The cellular entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) involves the association of its receptor binding domain (RBD) with human angiotensin converting enzyme 2 (hACE2) as the first crucial step. Efficient and reliable prediction of RBD-hACE2 binding affinity changes upon amino acid substitutions can be valuable for public health surveillance and monitoring potential spillover and adaptation into non-human species. Here, we introduce a convolutional neural network (CNN) model trained on protein sequence and structural features to predict experimental RBD-hACE2 binding affinities of 8,440 variants upon single and multiple amino acid substitutions in the RBD or ACE2. The model achieves a classification accuracy of 83.28% and a Pearson correlation coefficient of 0.85 between predicted and experimentally calculated binding affinities in five-fold cross-validation tests and predicts improved binding affinity for most circulating variants. We pro-actively used the CNN model to exhaustively screen for novel RBD variants with combinations of up to four single amino acid substitutions and suggested candidates with the highest improvements in RBD-ACE2 binding affinity for human and animal ACE2 receptors. We found that the binding affinity of RBD variants against animal ACE2s follows similar trends as those against human ACE2. White-tailed deer ACE2 binds to RBD almost as tightly as human ACE2 while cattle, pig, and chicken ACE2s bind weakly. The model allows testing whether adaptation of the virus for increased binding with other animals would cause concomitant increases in binding with hACE2 or decreased fitness due to adaptation to other hosts.

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Increased household transmission and immune escape of the SARS-CoV-2 Omicron variant compared to the Delta variant: evidence from Norwegian contact tracing and vaccination data

Cited by 18 publications

References 1 publication

Household Secondary Attack Rates of SARS-CoV-2 by Variant and Vaccination Status

Household Secondary Attack Rates of SARS-CoV-2 by Variant and Vaccination Status

SARS-CoV-2 Omicron disease burden in Australia following border reopening: a modelling analysis

A CNN model for predicting binding affinity changes between SARS-CoV-2 spike RBD variants and ACE2 homologues

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