The contribution of pre-symptomatic infection to the transmission dynamics of COVID-2019

Centre for Mathematical Modelling of Infectious Diseases nCoV Working Group; Yang Liu; Sebastian Funk; Stefan Flasche; Mark Jit

doi:10.12688/wellcomeopenres.15788.1

The contribution of pre-symptomatic infection to the transmission dynamics of COVID-2019

Centre for Mathematical Modelling of Infectious Diseases nCoV Working Group, Yang Liu^*, Sebastian Funk, Stefan Flasche, Mark Jit

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

47 Citations (Scopus)

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Abstract

Background: Pre-symptomatic transmission can be a key determinant of the effectiveness of containment and mitigation strategies for infectious diseases, particularly if interventions rely on syndromic case finding. For COVID-19, infections in the absence of apparent symptoms have been reported frequently alongside circumstantial evidence for asymptomatic or pre-symptomatic transmission. We estimated the potential contribution of pre-symptomatic cases to COVID-19 transmission.

Methods: Using the probability for symptom onset on a given day inferred from the incubation period, we attributed the serial interval reported from Shenzen, China, into likely pre-symptomatic and symptomatic transmission. We used the serial interval derived for cases isolated more than 6 days after symptom onset as the no active case finding scenario and the unrestricted serial interval as the active case finding scenario. We reported the estimate assuming no correlation between the incubation period and the serial interval alongside a range indicating alternative assumptions of positive and negative correlation.

Results: We estimated that 23% (range accounting for correlation: 12 - 28%) of transmissions in Shenzen may have originated from pre-symptomatic infections. Through accelerated case isolation following symptom onset, this percentage increased to 46% (21 - 46%), implying that about 35% of secondary infections among symptomatic cases have been prevented. These results were robust to using reported incubation periods and serial intervals from other settings.

Conclusions: Pre-symptomatic transmission may be essential to consider for containment and mitigation strategies for COVID-19.

Original language	English
Article number	58
Journal	Wellcome Open Research
Volume	5
DOIs	https://doi.org/10.12688/wellcomeopenres.15788.1
Publication status	Published - 1 Apr 2020

Bibliographical note

Funding Information:This work was supported by the Wellcome Trust through a Wellcome Senior Research Fellowship to Sebastian Funk [210758] and a Sir Henry Dale Wellcome Trust Fellowship to Stefan Flasche [208812]. Yang Liu was partially funded by the Bill & Melinda Gates Foundation [INV-003174] and the National Institute for Health Research (NIHR) [16/137/109] using UK aid from the UK
Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the UK Department of Health and Social Care. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Open Access: This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Publisher Copyright: © 2020 Liu Y et al.

Citation: : Liu Y, Centre for Mathematical Modelling of Infectious Diseases nCoV Working Group, Funk S and Flasche S. The contribution of pre-symptomatic infection to the transmission dynamics of COVID-2019 [version 1; peer review: 3 approved]
Wellcome Open Research 2020, 5:58

DOI: https://doi.org/10.12688/wellcomeopenres.15788.1

Keywords

COVID-19
Incubation period
Pre-symptomatic transmission
Serial interval

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.12688/wellcomeopenres.15788.1Licence: CC BY

Liu2020TheContributionOfPre-SymptomaticInfectionToTheTransmissionWellcomeOpenResFinal published version, 1.12 MBLicence: CC BY

Cite this

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title = "The contribution of pre-symptomatic infection to the transmission dynamics of COVID-2019",

abstract = "Background: Pre-symptomatic transmission can be a key determinant of the effectiveness of containment and mitigation strategies for infectious diseases, particularly if interventions rely on syndromic case finding. For COVID-19, infections in the absence of apparent symptoms have been reported frequently alongside circumstantial evidence for asymptomatic or pre-symptomatic transmission. We estimated the potential contribution of pre-symptomatic cases to COVID-19 transmission. Methods: Using the probability for symptom onset on a given day inferred from the incubation period, we attributed the serial interval reported from Shenzen, China, into likely pre-symptomatic and symptomatic transmission. We used the serial interval derived for cases isolated more than 6 days after symptom onset as the no active case finding scenario and the unrestricted serial interval as the active case finding scenario. We reported the estimate assuming no correlation between the incubation period and the serial interval alongside a range indicating alternative assumptions of positive and negative correlation. Results: We estimated that 23% (range accounting for correlation: 12 - 28%) of transmissions in Shenzen may have originated from pre-symptomatic infections. Through accelerated case isolation following symptom onset, this percentage increased to 46% (21 - 46%), implying that about 35% of secondary infections among symptomatic cases have been prevented. These results were robust to using reported incubation periods and serial intervals from other settings. Conclusions: Pre-symptomatic transmission may be essential to consider for containment and mitigation strategies for COVID-19.",

keywords = "COVID-19, Incubation period, Pre-symptomatic transmission, Serial interval",

author = "{Centre for Mathematical Modelling of Infectious Diseases nCoV Working Group} and Yang Liu and Sebastian Funk and Stefan Flasche and Mark Jit and Bosse, {Nikos I.} and Amy Gimma and Petra Klepac and Russell, {Timothy W.} and Fiona Sun and Alicia Rosello and Charlie Diamond and Kucharski, {Adam J.} and Houben, {Rein M.G.J.} and Munday, {James D.} and Thibaut Jambart and {John Edmunds}, W. and Pearson, {Carl A.B.} and {van Zandvoort}, Kevin and Eggo, {Rosalind M.} and Graham Medley and Hamish Gibbs and Sam Abbott and Joel Hellewell and Quilty, {Billy J.} and Jarvis, {Christopher I.} and Kiesha Prem and Samuel Clifford and Nicholas Davies",

note = "Funding Information:This work was supported by the Wellcome Trust through a Wellcome Senior Research Fellowship to Sebastian Funk [210758] and a Sir Henry Dale Wellcome Trust Fellowship to Stefan Flasche [208812]. Yang Liu was partially funded by the Bill & Melinda Gates Foundation [INV-003174] and the National Institute for Health Research (NIHR) [16/137/109] using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the UK Department of Health and Social Care. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Open Access: This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Publisher Copyright: {\textcopyright} 2020 Liu Y et al. Citation: : Liu Y, Centre for Mathematical Modelling of Infectious Diseases nCoV Working Group, Funk S and Flasche S. The contribution of pre-symptomatic infection to the transmission dynamics of COVID-2019 [version 1; peer review: 3 approved] Wellcome Open Research 2020, 5:58 DOI: https://doi.org/10.12688/wellcomeopenres.15788.1",

year = "2020",

month = apr,

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doi = "10.12688/wellcomeopenres.15788.1",

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TY - JOUR

T1 - The contribution of pre-symptomatic infection to the transmission dynamics of COVID-2019

AU - Centre for Mathematical Modelling of Infectious Diseases nCoV Working Group

AU - Liu, Yang

AU - Funk, Sebastian

AU - Flasche, Stefan

AU - Jit, Mark

AU - Bosse, Nikos I.

AU - Gimma, Amy

AU - Klepac, Petra

AU - Russell, Timothy W.

AU - Sun, Fiona

AU - Rosello, Alicia

AU - Diamond, Charlie

AU - Kucharski, Adam J.

AU - Houben, Rein M.G.J.

AU - Munday, James D.

AU - Jambart, Thibaut

AU - John Edmunds, W.

AU - Pearson, Carl A.B.

AU - van Zandvoort, Kevin

AU - Eggo, Rosalind M.

AU - Medley, Graham

AU - Gibbs, Hamish

AU - Abbott, Sam

AU - Hellewell, Joel

AU - Quilty, Billy J.

AU - Jarvis, Christopher I.

AU - Prem, Kiesha

AU - Clifford, Samuel

AU - Davies, Nicholas

N1 - Funding Information:This work was supported by the Wellcome Trust through a Wellcome Senior Research Fellowship to Sebastian Funk [210758] and a Sir Henry Dale Wellcome Trust Fellowship to Stefan Flasche [208812]. Yang Liu was partially funded by the Bill & Melinda Gates Foundation [INV-003174] and the National Institute for Health Research (NIHR) [16/137/109] using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the UK Department of Health and Social Care. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Open Access: This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Publisher Copyright: © 2020 Liu Y et al. Citation: : Liu Y, Centre for Mathematical Modelling of Infectious Diseases nCoV Working Group, Funk S and Flasche S. The contribution of pre-symptomatic infection to the transmission dynamics of COVID-2019 [version 1; peer review: 3 approved] Wellcome Open Research 2020, 5:58 DOI: https://doi.org/10.12688/wellcomeopenres.15788.1

PY - 2020/4/1

Y1 - 2020/4/1

N2 - Background: Pre-symptomatic transmission can be a key determinant of the effectiveness of containment and mitigation strategies for infectious diseases, particularly if interventions rely on syndromic case finding. For COVID-19, infections in the absence of apparent symptoms have been reported frequently alongside circumstantial evidence for asymptomatic or pre-symptomatic transmission. We estimated the potential contribution of pre-symptomatic cases to COVID-19 transmission. Methods: Using the probability for symptom onset on a given day inferred from the incubation period, we attributed the serial interval reported from Shenzen, China, into likely pre-symptomatic and symptomatic transmission. We used the serial interval derived for cases isolated more than 6 days after symptom onset as the no active case finding scenario and the unrestricted serial interval as the active case finding scenario. We reported the estimate assuming no correlation between the incubation period and the serial interval alongside a range indicating alternative assumptions of positive and negative correlation. Results: We estimated that 23% (range accounting for correlation: 12 - 28%) of transmissions in Shenzen may have originated from pre-symptomatic infections. Through accelerated case isolation following symptom onset, this percentage increased to 46% (21 - 46%), implying that about 35% of secondary infections among symptomatic cases have been prevented. These results were robust to using reported incubation periods and serial intervals from other settings. Conclusions: Pre-symptomatic transmission may be essential to consider for containment and mitigation strategies for COVID-19.

AB - Background: Pre-symptomatic transmission can be a key determinant of the effectiveness of containment and mitigation strategies for infectious diseases, particularly if interventions rely on syndromic case finding. For COVID-19, infections in the absence of apparent symptoms have been reported frequently alongside circumstantial evidence for asymptomatic or pre-symptomatic transmission. We estimated the potential contribution of pre-symptomatic cases to COVID-19 transmission. Methods: Using the probability for symptom onset on a given day inferred from the incubation period, we attributed the serial interval reported from Shenzen, China, into likely pre-symptomatic and symptomatic transmission. We used the serial interval derived for cases isolated more than 6 days after symptom onset as the no active case finding scenario and the unrestricted serial interval as the active case finding scenario. We reported the estimate assuming no correlation between the incubation period and the serial interval alongside a range indicating alternative assumptions of positive and negative correlation. Results: We estimated that 23% (range accounting for correlation: 12 - 28%) of transmissions in Shenzen may have originated from pre-symptomatic infections. Through accelerated case isolation following symptom onset, this percentage increased to 46% (21 - 46%), implying that about 35% of secondary infections among symptomatic cases have been prevented. These results were robust to using reported incubation periods and serial intervals from other settings. Conclusions: Pre-symptomatic transmission may be essential to consider for containment and mitigation strategies for COVID-19.

KW - COVID-19

KW - Incubation period

KW - Pre-symptomatic transmission

KW - Serial interval

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DO - 10.12688/wellcomeopenres.15788.1

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JF - Wellcome Open Research

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ER -

The contribution of pre-symptomatic infection to the transmission dynamics of COVID-2019

Abstract

Bibliographical note

Keywords

UN SDGs

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