Data-driven detection of concerning SARS-CoV-2 variants months in advance

Data-driven detection of concerning SARS-CoV-2 variants months in advance

Publication date: Jul 19, 2025

“We have developed a new analysis method for CoVerage that should help make antigenic changes in virus variants more visible,” explains McHardy. Early detection of VOCs is particularly important for vaccine development in order to ensure vaccine protection against new virus variants. DOI: 10. 1038/s41467-025-60231-4Since the start of the SARS-CoV-2 pandemic, several variants of the virus have developed into Variants of Concern (VOCs), as classified by the World Health Organization (WHO). The working group found that the new method enabled virus lines to be identified retrospectively as VOCs up to three months prior to the WHO designation. This involves comparing the amino acid changes occurring across the spike protein of viral strains from a given month. A statistical method is used to determine which viral strains have significantly changed their immune escape capacity. By March 2024 GISIAD had more than 16. 5 million SARS-CoV-2 sequences available. CoVerage analyzes the SARS-CoV-2 genome data by country of origin for strain dynamics and antigenic changes.

Concepts Keywords
Arboviruses Altered
Bioinformatician Communications
Worrisome Cov
Genome
Important
Interest
Months
Nature
Sars
Strains
Vaccine
Variants
Viral
Virus
Vocs

Semantics

Type Source Name
disease IDO process
disease MESH infections
disease MESH influenza
pathway KEGG Influenza A
disease IDO protein
disease IDO role
disease MESH dengue
disease IDO country

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