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
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
Journal
PLoS Biology
DOI
10.1371/journal.pbio.3002463
Method of Research
Computational simulation/modeling
Subject of Research
Not applicable
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
COI Statement
Competing Interests: see manuscript
