Presymptomatic transmission of SARS-CoV-2 infection: a secondary analysis using published data

This article has been Reviewed by the following groups

Read the full article

Abstract

To estimate the proportion of presymptomatic transmission of SARS-CoV-2 infection that can occur, and the timing of transmission relative to symptom onset.

Setting/design

Secondary analysis of international published data.

Data sources

Meta-analysis of COVID-19 incubation period and a rapid review of serial interval and generation time, which are published separately.

Participants

Data from China, the Islamic Republic of Iran, Italy, Republic of Korea, Singapore and Vietnam from December 2019 to May 2020.

Methods

Simulations were generated of incubation period and of serial interval or generation time. From these, transmission times relative to symptom onset, and the proportion of presymptomatic transmission, were estimated.

Outcome measures

Transmission time of SARS-CoV-2 relative to symptom onset and proportion of presymptomatic transmission.

Results

Based on 18 serial interval/generation time estimates from 15 papers, mean transmission time relative to symptom onset ranged from −2.6 (95% CI −3.0 to –2.1) days before infector symptom onset to 1.4 (95% CI 1.0 to 1.8) days after symptom onset. The proportion of presymptomatic transmission ranged from 45.9% (95% CI 42.9% to 49.0%) to 69.1% (95% CI 66.2% to 71.9%).

Conclusions

There is substantial potential for presymptomatic transmission of SARS-CoV-2 across a range of different contexts. This highlights the need for rapid case detection, contact tracing and quarantine. The transmission patterns that we report reflect the combination of biological infectiousness and transmission opportunities which vary according to context.

Article activity feed

  1. SciScore for 10.1101/2020.05.08.20094870: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    , Google Scholar [38], MedRxiv [39] and BioRxiv [40] with the following keywords: “Novel coronavirus” OR “SARS-CoV-2” OR “2019-nCoV” OR “COVID-19” AND “serial interval” OR “latent period” OR “incubation period” OR “generation time” OR “infectiousness” OR “pre-symptomatic” OR “asymptomatic”).
    Google Scholar
    suggested: (Google Scholar, RRID:SCR_008878)
    BioRxiv
    suggested: (bioRxiv, RRID:SCR_003933)
    The dynamic curated PubMed database “LitCovid” [41,42] was also monitored.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)

    Results from OddPub: Thank you for sharing your code and data.


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Griffin et al. [34] discuss drivers of this variation and the limitations in different approaches to estimating generation time and serial interval from transmission pairs. If people are quarantined once their symptoms become apparent, a greater proportion transmission will be pre-symptomatic. Whilst data relating to the early stages of the COVID-19 outbreak in Wuhan amount to only six pairs, we see a trend towards lower proportions of pre-symptomatic transmission in this context, as well as in the early stages of the outbreaks in Italy, possibly corresponding to relatively more transmission from symptomatic people in the early stages of disease incursion. Three other studies also highlight this contrast in the proportion of pre-symptomatic transmission in a different context. Zhao et al. [52] show that serial interval became shorter in Hong Kong and Shenzhen as time elapsed from initial cases, and suggest that this is due to increasing effectiveness of quarantining people with symptoms over time. Zhang [32] contrasts a mean transmission time of 2.3 days after symptoms in the early stages of the Wuhan outbreak (with relatively fewer quarantine measures) to a mean transmission time of 2.4 days before symptom onset amongst imported cases outside Wuhan. A study in Shenzhen [64] highlighted the valuable information that can be inferred from knowledge of when transmission occurred and when the infector was isolated. Serial interval was much shorter when the infectors were isolated...

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.