Understanding how fast SARS-CoV-2 variants transmit from household studies

Yang, Yang; Kenah, Eben

doi:10.1016/s1473-3099(22)00053-6

Cited by 8 publications

(7 citation statements)

References 12 publications

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“…On the other hand, the higher prevalence of obesity, a previously reported risk factor for severity with previous SARS-CoV-2 variants, including the ancestral variant, is consistent with previous data reporting obesity as a risk factor for severity [13]. These findings may have important implications for the updated use of pre-exposure monoclonal antibodies use [14] as well as COVID-19 vaccination recommendations. Initial estimates of the updated XBB.1.5 COVID-19 vaccine showed sustained vaccine efficacy against symptomatic JN.1 lineage infection [15].…”

Section: Discussionsupporting

confidence: 88%

Clinical phenotypes and outcomes associated with SARS-CoV-2 Omicron variant JN.1 in critically ill COVID-19 patients: a prospective, multicenter cohort study

de Prost,

Audureau,

Guillon

et al. 2024

Preprint

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A notable increase in severe cases of COVID-19, with significant hospitalizations due to the emergence and spread of JN.1 was observed worldwide in late 2023 and early 2024. During the study period (November 2022-January 2024), 56 JN.1- and 126 XBB-infected patients were prospectively enrolled in 40 French intensive care units. JN.1-infected patients were more likely to be obese (35.7% vs 20.8%; p=0.033) and less frequently immunosuppressed than others (20.4% vs 41.4%; p=0.010). JN.1-infected patients required invasive mechanical ventilation support in 29.1%, 87.5% of them received dexamethasone, 14.5% tocilizumab and none received monoclonal antibodies. Day-28 mortality of JN.1-infected patients was 14.6%.

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Section: Discussionsupporting

confidence: 88%

Clinical phenotypes and outcomes associated with SARS-CoV-2 Omicron variant JN.1 in critically ill COVID-19 patients: a prospective, multicenter cohort study

de Prost,

Audureau,

Guillon

et al. 2024

Preprint

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“…Anyway, BA.2.86 rapidly evolved and at the end of 2023 the JN.1 sublineage emerged becoming the predominant variant worldwide. JN.1 carries only one additional mutation in the RBD, L455S, compared to the ancestral BA.2.86 variant which resulted in decreased ACE2 affinity but enhanced immune evasion 35,36 . Future work will help to understand the classes of antibodies evaded and the germlines that are still able to retain neutralization against JN.1.…”

Section: Discussionmentioning

confidence: 99%

B cell maturation restored ancestral germlines to control Omicron BA.2.86

Paciello,

Pierleoni,

Pantano

et al. 2024

Preprint

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The unceasing interplay between SARS-CoV-2 and the human immune system has led to a continuous maturation of the virus and B cell response providing an opportunity to track their evolution in real time. We longitudinally analyzed the functional activity of almost 1,000 neutralizing human monoclonal antibodies (nAbs) isolated from vaccinated people, and from individuals with hybrid and super hybrid immunity (SH), developed after three mRNA vaccine doses and two breakthrough infections. The most potent neutralization and Fc functions against highly mutated variants, including BA.2.86, were found in the SH cohort. Despite different priming, epitope mapping revealed a convergent maturation of the functional antibody response. Neutralization was mainly driven by Class 1/2 nAbs while Fc functions were induced by Class 3/4 antibodies. Remarkably, broad neutralization was mediated by restored IGHV3-53/3-66 B cell germlines which, after heterogenous exposure to SARS-CoV-2 S proteins, increased their level of somatic hypermutations. Our study shows the resilience of the human immune system which restored previously expanded germlines and activated naive B cells to broaden the antibody repertoire of antibodies to control future SARS-CoV-2 variants.

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“…This new system is adaptable enough to react to changes in background noise (eg, community infection rates) and incubation times (eg, new SARS-CoV-2 variants). 19 Furthermore, we can easily adjust the parameters for different agents that may be under surveillance.…”

Section: Discussionmentioning

confidence: 99%

A new automated national register-based surveillance system for outbreaks in long-term care facilities in Norway detected three times more severe acute respiratory coronavirus virus 2 (SARS-CoV-2) clusters than traditional methods

Gravningen

Nymark

Wyller

et al. 2022

Infect. Control Hosp. Epidemiol.

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Objective: To develop and test a new automated surveillance system that can detect, define and characterize infection clusters, including coronavirus disease 2019 (COVID-19), in long-term care facilities (LTCFs) in Norway by combining existing national register data. Background: The numerous outbreaks in LTCFs during the COVID-19 pandemic highlighted the need for accurate and timely outbreak surveillance. As traditional methods were inadequate, we used severe acute respiratory coronavirus virus 2 (SARS-CoV-2) as a model to test automated surveillance. Methods: We conducted a nationwide study using data from the Norwegian preparedness register (Beredt C19) and defined the study population as an open cohort from January 2020 to December 2021. We analyzed clusters (≥3 individuals with positive SARS-CoV-2 test ≤14 days) by 4-month periods including cluster size, duration and composition, and residents’ mortality associated with clusters. Results: The study population included 173,907 individuals; 78% employees and 22% residents. Clusters were detected in 427 (43%) of 993 LTCFs. The median cluster size was 4–8 individuals (maximum, 50) by 4-month periods, with a median duration of 9–17 days. Employees represented 60%–82% of cases in clusters and were index cases in 60%–90%. In the last 4-month period of 2020, we detected 107 clusters (915 cases) versus 428 clusters (2,998 cases) in the last period of 2021. The 14-day all-cause mortality rate was higher in resident cases from the clusters. Varying the cluster definitions changed the number of clusters. Conclusion: Automated national surveillance for SARS-CoV-2 clusters in LTCFs is possible based on existing data sources and provides near real-time detailed information on size, duration, and composition of clusters. Thus, this system can assist in early outbreak detection and improve surveillance.

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Understanding how fast SARS-CoV-2 variants transmit from household studies

Cited by 8 publications

References 12 publications

Clinical phenotypes and outcomes associated with SARS-CoV-2 Omicron variant JN.1 in critically ill COVID-19 patients: a prospective, multicenter cohort study

Clinical phenotypes and outcomes associated with SARS-CoV-2 Omicron variant JN.1 in critically ill COVID-19 patients: a prospective, multicenter cohort study

B cell maturation restored ancestral germlines to control Omicron BA.2.86

A new automated national register-based surveillance system for outbreaks in long-term care facilities in Norway detected three times more severe acute respiratory coronavirus virus 2 (SARS-CoV-2) clusters than traditional methods

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