Quantifying the relationship between SARS-CoV-2 viral load and infectiousness

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...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Aurélien Marc, Marion Kerioui, François Blanquart, Julie Bertrand, Oriol Mitjà, Marc Corbacho-Monné, Michael Marks, Jeremie Guedj
Formato:	article
Lenguaje:	EN
Publicado:	eLife Sciences Publications Ltd 2021
Materias:	microbiology SARS-CoV-2 infectious diseases computational biology epidemiology Medicine R Science Q Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/fa4469bd37f34dfaa035cee38753eef9
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:fa4469bd37f34dfaa035cee38753eef9
record_format	dspace
spelling	oai:doaj.org-article:fa4469bd37f34dfaa035cee38753eef92021-11-17T14:27:41ZQuantifying the relationship between SARS-CoV-2 viral load and infectiousness10.7554/eLife.693022050-084Xe69302https://doaj.org/article/fa4469bd37f34dfaa035cee38753eef92021-09-01T00:00:00Zhttps://elifesciences.org/articles/69302https://doaj.org/toc/2050-084XThe 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 1010 copies per mL. The transmission probability peaked at symptom onset, with a mean probability of transmission of 29%, with large individual variations. The model also projects the effects of variants on disease transmission. Based on the current knowledge that viral load is increased by two- to eightfold with variants of concern and assuming no changes in the pattern of contacts across variants, the model predicts that larger viral load levels could lead to a relative increase in the probability of transmission of 24% to 58% in household contacts, and of 15% to 39% in non-household contacts.Aurélien MarcMarion KeriouiFrançois BlanquartJulie BertrandOriol MitjàMarc Corbacho-MonnéMichael MarksJeremie GuedjeLife Sciences Publications LtdarticlemicrobiologySARS-CoV-2infectious diseasescomputational biologyepidemiologyMedicineRScienceQBiology (General)QH301-705.5ENeLife, Vol 10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	microbiology SARS-CoV-2 infectious diseases computational biology epidemiology Medicine R Science Q Biology (General) QH301-705.5
spellingShingle	microbiology SARS-CoV-2 infectious diseases computational biology epidemiology Medicine R Science Q Biology (General) QH301-705.5 Aurélien Marc Marion Kerioui François Blanquart Julie Bertrand Oriol Mitjà Marc Corbacho-Monné Michael Marks Jeremie Guedj Quantifying the relationship between SARS-CoV-2 viral load and infectiousness
description	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 1010 copies per mL. The transmission probability peaked at symptom onset, with a mean probability of transmission of 29%, with large individual variations. The model also projects the effects of variants on disease transmission. Based on the current knowledge that viral load is increased by two- to eightfold with variants of concern and assuming no changes in the pattern of contacts across variants, the model predicts that larger viral load levels could lead to a relative increase in the probability of transmission of 24% to 58% in household contacts, and of 15% to 39% in non-household contacts.
format	article
author	Aurélien Marc Marion Kerioui François Blanquart Julie Bertrand Oriol Mitjà Marc Corbacho-Monné Michael Marks Jeremie Guedj
author_facet	Aurélien Marc Marion Kerioui François Blanquart Julie Bertrand Oriol Mitjà Marc Corbacho-Monné Michael Marks Jeremie Guedj
author_sort	Aurélien Marc
title	Quantifying the relationship between SARS-CoV-2 viral load and infectiousness
title_short	Quantifying the relationship between SARS-CoV-2 viral load and infectiousness
title_full	Quantifying the relationship between SARS-CoV-2 viral load and infectiousness
title_fullStr	Quantifying the relationship between SARS-CoV-2 viral load and infectiousness
title_full_unstemmed	Quantifying the relationship between SARS-CoV-2 viral load and infectiousness
title_sort	quantifying the relationship between sars-cov-2 viral load and infectiousness
publisher	eLife Sciences Publications Ltd
publishDate	2021
url	https://doaj.org/article/fa4469bd37f34dfaa035cee38753eef9
work_keys_str_mv	AT aurelienmarc quantifyingtherelationshipbetweensarscov2viralloadandinfectiousness AT marionkerioui quantifyingtherelationshipbetweensarscov2viralloadandinfectiousness AT francoisblanquart quantifyingtherelationshipbetweensarscov2viralloadandinfectiousness AT juliebertrand quantifyingtherelationshipbetweensarscov2viralloadandinfectiousness AT oriolmitja quantifyingtherelationshipbetweensarscov2viralloadandinfectiousness AT marccorbachomonne quantifyingtherelationshipbetweensarscov2viralloadandinfectiousness AT michaelmarks quantifyingtherelationshipbetweensarscov2viralloadandinfectiousness AT jeremieguedj quantifyingtherelationshipbetweensarscov2viralloadandinfectiousness
_version_	1718425456759275520

Quantifying the relationship between SARS-CoV-2 viral load and infectiousness

Ejemplares similares