Evidence map›Paper›PMID 34053264›Full record

ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2021

Dynamics of SARS-CoV-2 with waning immunity in the UK population.

Thomas Crellen, Li Pi, Emma L Davis, Timothy M Pollington, Tim C D Lucas, Diepreye Ayabina, Anna Borlase, Jaspreet Toor, Kiesha Prem, Graham F Medley and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.3field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 38 citations in OpenAlex.

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  12. Describing a landscape we are yet discovering.Advances in statistical analysis : AStA : a journal of the German Statistical Society · 2022
    Review
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  18. Epidemic interventions: insights from classic results.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Article
  19. Modelling that shaped the early COVID-19 pandemic response in the UK.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Thomas CrellenBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.
Li PiBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.
Emma L DavisBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.
Timothy M PollingtonBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.
Tim C D LucasBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.
Diepreye AyabinaBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.
Anna BorlaseBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.
Jaspreet ToorBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.
Kiesha PremLondon School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.
Graham F MedleyLondon School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.
Petra KlepacLondon School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.
T Déirdre HollingsworthBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.
University of Oxford · GBUniversity of London · GBUniversity of Warwick · GB

Funding

Medical Research Council MC_PC_19012Medical Research Council MR/R015600/1Wellcome Trust 215919/Z/19/Z
6 · The paper itself

Abstract

The dynamics of immunity are crucial to understanding the long-term patterns of the SARS-CoV-2 pandemic. Several cases of reinfection with SARS-CoV-2 have been documented 48-142 days after the initial infection and immunity to seasonal circulating coronaviruses is estimated to be shorter than 1 year. Using an age-structured, deterministic model, we explore potential immunity dynamics using contact data from the UK population. In the scenario where immunity to SARS-CoV-2 lasts an average of three months for non-hospitalized individuals, a year for hospitalized individuals, and the effective reproduction number after lockdown ends is 1.2 (our worst-case scenario), we find that the secondary peak occurs in winter 2020 with a daily maximum of 387 000 infectious individuals and 125 000 daily new cases; threefold greater than in a scenario with permanent immunity. Our models suggest that longitudinal serological surveys to determine if immunity in the population is waning will be most informative when sampling takes place from the end of the lockdown in June until autumn 2020. After this period, the proportion of the population with antibodies to SARS-CoV-2 is expected to increase due to the secondary wave. Overall, our analysis presents considerations for policy makers on the longer-term dynamics of SARS-CoV-2 in the UK and suggests that strategies designed to achieve herd immunity may lead to repeated waves of infection as immunity to reinfection is not permanent. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Indexed as

PandemicsBasic Reproduction NumberCommunicable Disease ControlCOVID-19HumansSARS-CoV-2United KingdomCOVID-19immunityinfectious disease epidemiologymathematical modellingSARS-CoV-2UK

Identifiers

PMID34053264
PMCPMC8165597
OpenAlexW3044575348

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.