Heterogeneity in transmissibility and shedding SARS-CoV-2 via droplets and aerosols

  1. Paul Z Chen
  2. Niklas Bobrovitz
  3. Zahra Premji
  4. Marion Koopmans
  5. David N Fisman
  6. Frank X Gu

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Abstract

Which virological factors mediate overdispersion in the transmissibility of emerging viruses remains a long-standing question in infectious disease epidemiology.

Methods:

Here, we use systematic review to develop a comprehensive dataset of respiratory viral loads (rVLs) of SARS-CoV-2, SARS-CoV-1 and influenza A(H1N1)pdm09. We then comparatively meta-analyze the data and model individual infectiousness by shedding viable virus via respiratory droplets and aerosols.

Results:

The analyses indicate heterogeneity in rVL as an intrinsic virological factor facilitating greater overdispersion for SARS-CoV-2 in the COVID-19 pandemic than A(H1N1)pdm09 in the 2009 influenza pandemic. For COVID-19, case heterogeneity remains broad throughout the infectious period, including for pediatric and asymptomatic infections. Hence, many COVID-19 cases inherently present minimal transmission risk, whereas highly infectious individuals shed tens to thousands of SARS-CoV-2 virions/min via droplets and aerosols while breathing, talking and singing. Coughing increases the contagiousness, especially in close contact, of symptomatic cases relative to asymptomatic ones. Infectiousness tends to be elevated between 1 and 5 days post-symptom onset.

Conclusions:

Intrinsic case variation in rVL facilitates overdispersion in the transmissibility of emerging respiratory viruses. Our findings present considerations for disease control in the COVID-19 pandemic as well as future outbreaks of novel viruses.

Funding:

Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant program, NSERC Senior Industrial Research Chair program and the Toronto COVID-19 Action Fund.

Article activity feed

  1. Version published to 10.7554/elife.65774 on eLife
  2. ScreenIT

    SciScore for 10.1101/2020.10.13.20212233: (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
    The meta-analyses were conducted using STATA
    STATA
    suggested: (Stata, RRID:SCR_012763)
    14.2 (StataCorp LLC, College Station, Texas, USA).
    StataCorp
    suggested: (Stata, RRID:SCR_012763)
    (2) and its 95% CI was performed using the Distribution Fitter application in Matlab R2019b (MathWorks, Inc., Natick, Massachusetts, USA)
    Matlab
    suggested: (MATLAB, RRID:SCR_001622)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study has limitations. The systematic search found a limited number of studies reporting quantitative specimen measurements from the presymptomatic period, meaning these estimates may be sensitive to sampling bias. Although additional studies have reported semiquantitative metrics (cycle thresholds), these data were excluded because they cannot be compared on an absolute scale due to batch effects (36), limiting use in compound analyses. Furthermore, this study considered population-level estimates of the infectious periods, viability proportions and rate profiles for respiratory particles, which omit individual or environmental variation. Distinctions in phonetic tendencies and, especially for young children, respiratory capacity lead to variation in particle emission rates (37). Some patients shed SARS-CoV-2 with diminishing viability soon after symptom onset (21), whereas others produce replication-competent virus for weeks (38). It remains unclear how case characteristics and environmental factors affect the viability dynamics of SARS-CoV-2. Taken together, our findings provide a potential path forward for disease control. They support aerosol spread as a transmission mode for SARS-CoV-2, including for conditional superspreading by highly infectious cases. However, with short durations of stay in well-ventilated areas, the exposure risk for aerosols, including long-range and buoyant ones, remains correlated with proximity to infectious cases (2, 4). Strategies to abat...

    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.
    • Thank you for including a protocol registration statement.

    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.

  3. Version published to 10.1101/2020.10.13.20212233v3 on medRxiv
  4. Version published to 10.1101/2020.10.13.20212233v2 on medRxiv
  5. ScreenIT

    SciScore for 10.1101/2020.10.13.20212233: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

    Our study has limitations. The systematic search found a limited number of studies reporting quantitative specimen measurements from the presymptomatic period, meaning these estimates may be sensitive to sampling bias. Although additional studies have reported semiquantitative metrics (cycle thresholds), these data were excluded because they cannot be compared on an absolute scale due to batch effects34, limiting use in compound analyses. Furthermore, our analyses considered population-level estimates of the infectious periods and viability proportions, which omit individual variation in the dynamics of virus viability. Some patients shed SARS-CoV-2 with diminishing viability soon after symptom onset13, while others produce replication-competent virus for weeks35. It remains unelucidated how case characteristics and environmental factors affect the viability dynamics of SARS-CoV-2. Taken together, our findings provide a potential path forward for disease control. They highlight the disproportionate role of high-risk cases, settings and circumstances in propelling the COVID-19 pandemic. Since highly infectious cases, regardless of age or symptomatology, can rapidly shed SARS-CoV-2 via both droplets and aerosols, airborne spread should also be recognized as a transmission risk, including for superspreading. Strategies to abate infection should limit crowd numbers and duration of stay while reinforcing distancing and then widespread mask usage; well-ventilated settings can be re...

    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.

    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.

  6. Version published to 10.1101/2020.10.13.20212233v1 on medRxiv