News Release

The emergence of successive SARS-CoV-2 variants of concern during 2020-22 created a need to understand the drivers of such growth

This study uses a Bayesian model to reveal how a set of key covariates affect viral kinetics at both individual and population levels

Peer-Reviewed Publication

PLOS

The emergence of successive SARS-CoV-2 variants of concern during 2020-22 created a need to understand the drivers of such growth

image: 

Schematic of the study design and modelling procedure. Typical Ct value data and model fits for 2 representative individuals with different covariates.

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Credit: Russell TW et al., 2024, PLOS Biology, CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/)

The emergence of successive SARS-CoV-2 variants of concern during 2020-22 created a need to understand the drivers of such growth; this study uses a Bayesian model to reveal how a set of key covariates (the infecting variant, symptom status, age and number of prior exposures) affect viral kinetics at both individual and population levels

 

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In your coverage, please use this URL to provide access to the freely available paper in PLOS Biology:   http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3002463

Article Title: Combined analyses of within-host SARS-CoV-2 viral kinetics and information on past exposures to the virus in a human cohort identifies intrinsic differences of Omicron and Delta variants

Author Countries: United Kingdom

Funding: see manuscript


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