Evidence map›Paper›PMID 33620317›Full record

ArticleeLife2021

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

Ashish Goyal, Daniel B Reeves, E Fabian Cardozo-Ojeda, Joshua T Schiffer, Bryan T Mayer

Abstract read
In one paragraph

Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers.

0numbers the graph read from it
0cells of the map it votes in
137citing papers in PubMed
–field-weighted citation impact
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

137 citing papers in PubMed.

  1. Trial
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  10. Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  11. Article
  12. Article
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  14. Article
  15. Article
  16. Viral Dynamic Models During COVID-19: Are We Ready for the Next Pandemic?CPT: pharmacometrics & systems pharmacology · 2025
    Review
  17. Article
  18. Endogenous competition and the underrealized reproduction of infectious diseases.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  19. Article
  20. Article

77 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Ashish GoyalVaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, United States.
Daniel B ReevesVaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, United States.ORCID 0000-0001-5684-9538
E Fabian Cardozo-OjedaVaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, United States.
Joshua T SchifferVaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, United States.ORCID 0000-0002-2598-1621
Bryan T MayerVaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, United States.

Funding

SDMC: HIV Vaccine Trials NetworkUM1AI068635 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Peter B. Gilbert, Yunda Huang · 2011 to 2026
$385.9M
Immunoprotective Properties of Tissue-resident Memory T Cells in Mice and Humans within Mucosal SitesR01AI121129 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI LUND, JENNIFER M, PRLIC, MARTIN · 2016 to 2022
$5.0M
Simulating persistence and elimination of the HIV reservoirK25AI155224 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI REEVES, DANIEL · 2020 to 2024
$581k
NIAID NIH HHS K25 AI155224NIAID NIH HHS R01 AI121129NIAID NIH HHS UM1 AI068635
6 · The paper itself

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 1 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 toward 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.

Indexed as

Carrier StateViral LoadVirus SheddingAerosolsBasic Reproduction NumberChinaComputer SimulationContact TracingCOVID-19HumansInfluenza, HumanModels, TheoreticalPandemicsProbabilitySARS-CoV-2Time FactorsAerosolsepidemiologyglobal healthhumaninfectious diseasemathematical modelingmicrobiologySARS-CoV-2viral dynamics

Identifiers

PMID33620317
PMCPMC7929560

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.