Quantifying the relationship between SARS-CoV-2 viral load and infectiousness.
SARS-CoV-2
computational biology
epidemiology
human
infectious disease
infectious diseases
microbiology
Journal
eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614
Informations de publication
Date de publication:
27 09 2021
27 09 2021
Historique:
received:
11
04
2021
accepted:
01
09
2021
entrez:
27
9
2021
pubmed:
28
9
2021
medline:
6
10
2021
Statut:
epublish
Résumé
The relationship between SARS-CoV-2 viral load and infectiousness is poorly known. Using data from a cohort of cases and high-risk contacts, we reconstructed viral load at the time of contact and inferred the probability of infection. The effect of viral load was larger in household contacts than in non-household contacts, with a transmission probability as large as 48% when the viral load was greater than 10
Identifiants
pubmed: 34569939
doi: 10.7554/eLife.69302
pii: 69302
pmc: PMC8476126
doi:
pii:
Substances chimiques
COVID-19 Vaccines
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Bill & Melinda Gates Foundation
ID : INV-017335
Pays : United States
Organisme : European Research Council
ID : ERC Starting Grant under the European Union's Horizon 2020 research and innovation programme
Pays : International
Organisme : Bill & Melinda Gates Foundation
ID : INV-017335
Pays : United States
Informations de copyright
© 2021, Marc et al.
Déclaration de conflit d'intérêts
AM, MK, FB, JB, OM, MC, MM, JG No competing interests declared
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