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In this study, we evaluated the impact of viral variant, in addition to other variables, on within-host viral burden, by analysing cycle threshold (Ct) values derived from nose and throat swabs, collected as part of the UK COVID-19 Infection Survey. Because viral burden distributions determined from community survey data can be biased due to the impact of variant epidemiology on the time-since-infection of samples, we developed a method to explicitly adjust observed Ct value distributions to account for the expected bias. By analysing the adjusted Ct values using partial least squares regression, we found that among unvaccinated individuals with no known prior exposure, viral burden was 44% lower among Alpha variant infections, compared to those with the predecessor strain, B.1.177. Vaccination reduced viral burden by 67%, and among vaccinated individuals, viral burden was 286% higher among Delta variant, compared to Alpha variant, infections. In addition, viral burden increased by 17% for every 10-year age increment of the infected individual. In summary, within-host viral burden increases with age, is reduced by vaccination, and is influenced by the interplay of vaccination status and viral variant.

Original publication

DOI

10.1371/journal.ppat.1011461

Type

Journal article

Journal

PLoS pathogens

Publication Date

08/2023

Volume

19

Addresses

Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, United Kingdom.

Keywords

COVID-19 Genomics UK (COG-UK) consortium, Humans, Vaccination, Viral Load, Selection Bias, COVID-19, SARS-CoV-2