Prevalence of persistent SARS-CoV-2 in a large community surveillance study

Mahan Ghafari(Open Data Institute), Matthew Hall(Open Data Institute), Tanya Golubchik(The University of Sydney), Daniel Ayoubkhani(Office for National Statistics), Thomas House(University of Manchester), George MacIntyre-Cockett(Centre for Human Genetics), Helen Fryer(Open Data Institute), Laura Thomson(Open Data Institute), Anel Nurtay(Open Data Institute), Steven A. Kemp(Open Data Institute), Luca Ferretti(Open Data Institute), David Buck(Centre for Human Genetics), Angie Green(Centre for Human Genetics), Amy Trebes(Centre for Human Genetics), Paolo Piazza(Centre for Human Genetics), Lorne Lonie(Centre for Human Genetics), Ruth Studley(Office for National Statistics), Emma Rourke(Office for National Statistics), Darren Smith(Northumbria University), Matthew Bashton(Northumbria University), Andrew Nelson(Northumbria University), Matthew Crown(Northumbria University), Clare M. McCann(Northumbria University), Gregory R. Young(Northumbria University), Rui Andre Nunes dos Santos(Northumbria University), Zack Richards(Northumbria University), Mohammad Adnan Tariq(Northumbria University), Roberto Cahuantzi(Office for National Statistics), COVID-19 Infection Survey Group(Wellcome Sanger Institute), Jeff Barrett(Centre for Human Genetics), Christophe Fraser(Centre for Human Genetics), David Bonsall(Centre for Human Genetics), Ann Sarah Walker(National Institute for Health and Care Research), Katrina Lythgoe(University of Oxford)
Nature
February 21, 2024
Cited by 150Open Access
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Abstract

Abstract Persistent SARS-CoV-2 infections may act as viral reservoirs that could seed future outbreaks 1–5 , give rise to highly divergent lineages 6–8 and contribute to cases with post-acute COVID-19 sequelae (long COVID) 9,10 . However, the population prevalence of persistent infections, their viral load kinetics and evolutionary dynamics over the course of infections remain largely unknown. Here, using viral sequence data collected as part of a national infection survey, we identified 381 individuals with SARS-CoV-2 RNA at high titre persisting for at least 30 days, of which 54 had viral RNA persisting at least 60 days. We refer to these as ‘persistent infections’ as available evidence suggests that they represent ongoing viral replication, although the persistence of non-replicating RNA cannot be ruled out in all. Individuals with persistent infection had more than 50% higher odds of self-reporting long COVID than individuals with non-persistent infection. We estimate that 0.1–0.5% of infections may become persistent with typically rebounding high viral loads and last for at least 60 days. In some individuals, we identified many viral amino acid substitutions, indicating periods of strong positive selection, whereas others had no consensus change in the sequences for prolonged periods, consistent with weak selection. Substitutions included mutations that are lineage defining for SARS-CoV-2 variants, at target sites for monoclonal antibodies and/or are commonly found in immunocompromised people 11–14 . This work has profound implications for understanding and characterizing SARS-CoV-2 infection, epidemiology and evolution.


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