Broadening symptom criteria improves early case identification in SARS-CoV-2 contacts.


Journal

The European respiratory journal
ISSN: 1399-3003
Titre abrégé: Eur Respir J
Pays: England
ID NLM: 8803460

Informations de publication

Date de publication:
07 2022
Historique:
received: 22 08 2021
accepted: 11 11 2021
pubmed: 27 11 2021
medline: 12 7 2022
entrez: 26 11 2021
Statut: epublish

Résumé

The success of case isolation and contact tracing for the control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission depends on the accuracy and speed of case identification. We assessed whether inclusion of additional symptoms alongside three canonical symptoms (CS), Two prospective longitudinal London (UK)-based cohorts of community SARS-CoV-2 contacts, recruited within 5 days of exposure, provided independent training and test datasets. Infected and uninfected contacts completed daily symptom diaries from the earliest possible time-points. Diagnostic information gained by adding symptoms to the CS was quantified using likelihood ratios and area under the receiver operating characteristic curve. Improvements in sensitivity and time to detection were compared with penalties in terms of specificity and number needed to test. Of 529 contacts within two cohorts, 164 (31%) developed PCR-confirmed infection and 365 (69%) remained uninfected. In the training dataset (n=168), 29% of infected contacts did not report the CS. Four symptoms (sore throat, muscle aches, headache and appetite loss) were identified as early-predictors (EP) which added diagnostic value to the CS. The broadened symptom criterion "≥1 of the CS, or ≥2 of the EP" identified PCR-positive contacts in the test dataset on average 2 days earlier after exposure (p=0.07) than "≥1 of the CS", with only modest reduction in specificity (5.7%). Broadening symptom criteria to include individuals with at least two of muscle aches, headache, appetite loss and sore throat identifies more infections and reduces time to detection, providing greater opportunities to prevent SARS-CoV-2 transmission.

Sections du résumé

BACKGROUND
The success of case isolation and contact tracing for the control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission depends on the accuracy and speed of case identification. We assessed whether inclusion of additional symptoms alongside three canonical symptoms (CS),
METHODS
Two prospective longitudinal London (UK)-based cohorts of community SARS-CoV-2 contacts, recruited within 5 days of exposure, provided independent training and test datasets. Infected and uninfected contacts completed daily symptom diaries from the earliest possible time-points. Diagnostic information gained by adding symptoms to the CS was quantified using likelihood ratios and area under the receiver operating characteristic curve. Improvements in sensitivity and time to detection were compared with penalties in terms of specificity and number needed to test.
RESULTS
Of 529 contacts within two cohorts, 164 (31%) developed PCR-confirmed infection and 365 (69%) remained uninfected. In the training dataset (n=168), 29% of infected contacts did not report the CS. Four symptoms (sore throat, muscle aches, headache and appetite loss) were identified as early-predictors (EP) which added diagnostic value to the CS. The broadened symptom criterion "≥1 of the CS, or ≥2 of the EP" identified PCR-positive contacts in the test dataset on average 2 days earlier after exposure (p=0.07) than "≥1 of the CS", with only modest reduction in specificity (5.7%).
CONCLUSIONS
Broadening symptom criteria to include individuals with at least two of muscle aches, headache, appetite loss and sore throat identifies more infections and reduces time to detection, providing greater opportunities to prevent SARS-CoV-2 transmission.

Identifiants

pubmed: 34824057
pii: 13993003.02308-2021
doi: 10.1183/13993003.02308-2021
pmc: PMC8620106
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Medical Research Council
ID : MC_PC_19078
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/R015600/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/R021643/1
Pays : United Kingdom
Organisme : Department of Health
ID : NIHR200927
Pays : United Kingdom

Informations de copyright

Copyright ©The authors 2022.

Déclaration de conflit d'intérêts

Conflict of interest: No competing interests were declared by any of the study authors.

Auteurs

Hamish Houston (H)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.
H. Houston and S. Hakki contributed equally.

Seran Hakki (S)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.
H. Houston and S. Hakki contributed equally.

Timesh D Pillay (TD)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Kieran Madon (K)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Nieves Derqui-Fernandez (N)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Aleksandra Koycheva (A)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Anika Singanayagam (A)

National Infection Service, Public Health England, London, UK.

Joe Fenn (J)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Rhia Kundu (R)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Emily Conibear (E)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Robert Varro (R)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Jessica Cutajar (J)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Valerie Quinn (V)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Lulu Wang (L)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Janakan S Narean (JS)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Mica R Tolosa-Wright (MR)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Jack Barnett (J)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.

Onn Min Kon (OM)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK.
Tuberculosis Service, Imperial College Healthcare NHS Trust, London, UK.

Richard Tedder (R)

Molecular Diagnostics Unit, Imperial College London, London, UK.

Graham Taylor (G)

Section of Virology, Dept of Infectious Disease, Imperial College London, London, UK.

Maria Zambon (M)

National Infection Service, Public Health England, London, UK.

Neil Ferguson (N)

Dept of Infectious Disease Epidemiology, Faculty of Medicine, Imperial College London, London, UK.

Jake Dunning (J)

National Infection Service, Public Health England, London, UK.
NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Oxford, Oxford, UK.

Jonathan J Deeks (JJ)

Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
H. Houston and S. Hakki contributed equally.

Ajit Lalvani (A)

NIHR Health Protection Research Unit in Respiratory Infections, Imperial College London, London, UK a.lalvani@imperial.ac.uk.
J.J. Deeks and A. Lalvani contributed equally.

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