Viral load and contact heterogeneity predict SARS-CoV-2 transmission and super-spreading events

  1. Ashish Goyal
  2. Daniel B Reeves
  3. E Fabian Cardozo-Ojeja
  4. Joshua T Schiffer  Is a corresponding author
  5. Bryan T Mayer
  1. Fred Hutchinson Cancer Research Center, United States

Abstract

SARS-CoV-2 is difficult to contain because many transmissions occur during pre-symptomatic infection. Unlike influenza, most SARS-CoV-2 infected people do not transmit while a small percentage infect large numbers of people. We designed mathematical models which link observed viral loads with epidemiologic features of each virus, including distribution of transmissions attributed to each infected person and duration between symptom onset in the transmitter and secondarily infected person. We identify that people infected with SARS-CoV-2 or influenza can be highly contagious for less than one day, congruent with peak viral load. SARS-CoV-2 super-spreader events occur when an infected person is shedding at a very high viral load and has a high number of exposed contacts. The higher predisposition of SARS-CoV-2 towards super-spreading events cannot be attributed to additional weeks of shedding relative to influenza. Rather, a person infected with SARS-CoV-2 exposes more people within equivalent physical contact networks, likely due to aerosolization.

Data availability

The original data and code is shared at: https://github.com/ashish2goyal/SARS_CoV_2_Super_Spreader_Event

Article and author information

Author details

  1. Ashish Goyal

    Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    No competing interests declared.
  2. Daniel B Reeves

    Vaccine and Infectious Diseases, Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5684-9538
  3. E Fabian Cardozo-Ojeja

    Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    No competing interests declared.
  4. Joshua T Schiffer

    Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    For correspondence
    jschiffe@fredhutch.org
    Competing interests
    Joshua T Schiffer, Reviewing editor, eLifeIs on the trial planning committee for a Gilead funded trial of remdesivir but is not reimbursed for this activity.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2598-1621
  5. Bryan T Mayer

    Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    No competing interests declared.

Funding

National Institute of Allergy and Infectious Diseases (R01 AI121129-05S1)

  • Joshua T Schiffer

Council of State and Territorial Epidemiologists (Inform Public Health Decision Making Funding Opportunity)

  • Joshua T Schiffer

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2021, Goyal et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Ashish Goyal
  2. Daniel B Reeves
  3. E Fabian Cardozo-Ojeja
  4. Joshua T Schiffer
  5. Bryan T Mayer
(2021)
Viral load and contact heterogeneity predict SARS-CoV-2 transmission and super-spreading events
eLife 10:e63537.
https://doi.org/10.7554/eLife.63537

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https://doi.org/10.7554/eLife.63537

Further reading

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    Research Article

    Background:

    In many settings, a large fraction of the population has both been vaccinated against and infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Hence, quantifying the protection provided by post-infection vaccination has become critical for policy. We aimed to estimate the protective effect against SARS-CoV-2 reinfection of an additional vaccine dose after an initial Omicron variant infection.

    Methods:

    We report a retrospective, population-based cohort study performed in Shanghai, China, using electronic databases with information on SARS-CoV-2 infections and vaccination history. We compared reinfection incidence by post-infection vaccination status in individuals initially infected during the April–May 2022 Omicron variant surge in Shanghai and who had been vaccinated before that period. Cox models were fit to estimate adjusted hazard ratios (aHRs).

    Results:

    275,896 individuals were diagnosed with real-time polymerase chain reaction-confirmed SARS-CoV-2 infection in April–May 2022; 199,312/275,896 were included in analyses on the effect of a post-infection vaccine dose. Post-infection vaccination provided protection against reinfection (aHR 0.82; 95% confidence interval 0.79–0.85). For patients who had received one, two, or three vaccine doses before their first infection, hazard ratios for the post-infection vaccination effect were 0.84 (0.76–0.93), 0.87 (0.83–0.90), and 0.96 (0.74–1.23), respectively. Post-infection vaccination within 30 and 90 days before the second Omicron wave provided different degrees of protection (in aHR): 0.51 (0.44–0.58) and 0.67 (0.61–0.74), respectively. Moreover, for all vaccine types, but to different extents, a post-infection dose given to individuals who were fully vaccinated before first infection was protective.

    Conclusions:

    In previously vaccinated and infected individuals, an additional vaccine dose provided protection against Omicron variant reinfection. These observations will inform future policy decisions on COVID-19 vaccination in China and other countries.

    Funding:

    This study was funded the Key Discipline Program of Pudong New Area Health System (PWZxk2022-25), the Development and Application of Intelligent Epidemic Surveillance and AI Analysis System (21002411400), the Shanghai Public Health System Construction (GWVI-11.2-XD08), the Shanghai Health Commission Key Disciplines (GWVI-11.1-02), the Shanghai Health Commission Clinical Research Program (20214Y0020), the Shanghai Natural Science Foundation (22ZR1414600), and the Shanghai Young Health Talents Program (2022YQ076).