Katalog Plus
Bibliothek der Frankfurt UAS
Bald neuer Katalog: sichern Sie sich schon vorab Ihre persönlichen Merklisten im Nutzerkonto: Anleitung.
Dieses Ergebnis aus BASE kann Gästen nicht angezeigt werden.  Login für vollen Zugriff.

Integrated Analysis of the 2022 SARS-CoV-2 Omicron Lineage Replacement Dynamics in Connecticut, US

Title: Integrated Analysis of the 2022 SARS-CoV-2 Omicron Lineage Replacement Dynamics in Connecticut, US
Authors: Chen, NFG; Pham, K; Chaguza, C; Lopes, R; Klaassen, F; Kalinich, CC; Kerantzas, N; Pandya, S; Ferguson, D; Schulz, W; Weinberger, DM; Pitzer, VE; Warren, JL; Grubaugh, ND; Hahn, AM
Publisher Information: MDPI AG
Publication Year: 2025
Collection: The University of Melbourne: Digital Repository
Description: In 2022, consecutive sweeps of highly transmissible SARS-CoV-2 Omicron-derived lineages (B.1.1.529*) maintained viral transmission despite extensive antigen exposure from both vaccinations and infections. To better understand Omicron variant emergence in the context of the dynamic fitness landscape of 2022, we aimed to explore putative drivers behind SARS-CoV-2 lineage replacements. Variant fitness is determined through its ability to either outrun previously dominant lineages or more efficiently circumvent host immune responses to previous infections and vaccinations. By analyzing data collected through our local genomic surveillance program from Connecticut, USA, we compared emerging Omicron lineages' growth rates, estimated infections, effective reproductive rates, average viral copy numbers, and likelihood for causing infections in recently vaccinated individuals. We find that newly emerging Omicron lineages outcompeted dominant lineages through a combination of enhanced viral shedding or advanced immune escape depending on the population-level exposure state. This analysis integrates individual-level sequencing data with demographic, vaccination, laboratory, and epidemiological data and provides further insights into host-pathogen dynamics beyond public aggregate data.
Document Type: article in journal/newspaper
Language: English
ISSN: 1999-4915
Relation: pii: v17071020; https://hdl.handle.net/11343/363176
Availability: https://hdl.handle.net/11343/363176
Rights: https://creativecommons.org/licenses/by/4.0 ; CC BY
Accession Number: edsbas.9F29D767
Database: BASE