Evidence map›Paper›PMID 32831176›Full record

ArticleeLife2020

The contribution of asymptomatic SARS-CoV-2 infections to transmission on the Diamond Princess cruise ship.

Jon C Emery, Timothy W Russell, Yang Liu, Joel Hellewell, Carl Ab Pearson, CMMID COVID-19 Working Group, Gwenan M Knight, Rosalind M Eggo, Adam J Kucharski, Sebastian Funk and 2 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05290792 (Use of Wearable Sensors for Early Detection and Tracking of Viral Respiratory Tract Infections), which is not on this map. Cited by 58 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 3 pooled it
2.9field-weighted citation impact, top 6% 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.

NCT05290792 nacompletednot on this mapstarted 2021, after this paper: background citation

Use of Wearable Sensors for Early Detection and Tracking of Viral Respiratory Tract Infections: The WE SENSE Study

TypeinterventionalSponsorEmily McDonaldRan2021 to 2022Enrolled56ConditionsViral Respiratory Tract Infection, InfluenzaArmsAdministration of FluMist (Live Attenuated Influenza Vaccine)
3 · Its place in the literature

Who cites it

58 citing papers in PubMed, 3 syntheses or guidelines pooled it, 92 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Systematic Review on Outbreaks of SARS-CoV-2 on Cruise, Navy and Cargo Ships.International journal of environmental research and public health · 2021
    Pooled it
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  18. Role of Asymptomatic COVID-19 Cases in Viral Transmission: Findings From a Hierarchical Community Contact Network Model.IEEE transactions on automation science and engineering : a publication of the IEEE Robotics and Automation Society · 2022
    Article
  19. Contrasting SARS-CoV-2 epidemics in Singapore: cohort studies in migrant workers and the general population.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022
    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 1 institution in 1 country.

Jon C EmeryCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID https://orcid.org/0000-0001-6644-7604
Timothy W RussellCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Yang LiuCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Joel HellewellCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Carl Ab PearsonCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
CMMID COVID-19 Working GroupCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Gwenan M KnightCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID http://orcid.org/0000-0002-7263-9896
Rosalind M EggoCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Adam J KucharskiCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID http://orcid.org/0000-0001-8814-9421
Sebastian FunkCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID http://orcid.org/0000-0002-2842-3406
Stefan FlascheCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Rein Mgj HoubenCentre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID https://orcid.org/0000-0003-4132-7467
London School of Hygiene & Tropical Medicine · GB

Funding

European Research Council Action Number 757699Medical Research Council MC_PC 19065Medical Research Council MC_PC_19065Medical Research Council MR/P014658/1Wellcome Trust
6 · The paper itself

Abstract

A key unknown for SARS-CoV-2 is how asymptomatic infections contribute to transmission. We used a transmission model with asymptomatic and presymptomatic states, calibrated to data on disease onset and test frequency from the Diamond Princess cruise ship outbreak, to quantify the contribution of asymptomatic infections to transmission. The model estimated that 74% (70-78%, 95% posterior interval) of infections proceeded asymptomatically. Despite intense testing, 53% (51-56%) of infections remained undetected, most of them asymptomatic. Asymptomatic individuals were the source for 69% (20-85%) of all infections. The data did not allow identification of the infectiousness of asymptomatic infections, however low ranges (0-25%) required a net reproduction number for individuals progressing through presymptomatic and symptomatic stages of at least 15. Asymptomatic SARS-CoV-2 infections may contribute substantially to transmission. Control measures, and models projecting their potential impact, need to look beyond the symptomatic cases if they are to understand and address ongoing transmission.

Indexed as

Asymptomatic DiseasesBetacoronavirusCalibrationCoronavirus InfectionsCOVID-19HumansIncidenceModels, StatisticalPandemicsPneumonia, ViralSARS-CoV-2Shipsasymptomatic infectionsCOVID-19epidemiologyglobal healthhumaninfectious diseasemicrobiologySARS-CoV-2subclinical infectionstransmission

Identifiers

PMID32831176
PMCPMC7527238
OpenAlexW3080956330

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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.