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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8476126/ https://www.ncbi.nlm.nih.gov/pubmed/34569939 http://dx.doi.org/10.7554/eLife.69302 |
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author | Marc, Aurélien Kerioui, Marion Blanquart, François Bertrand, Julie Mitjà, Oriol Corbacho-Monné, Marc Marks, Michael Guedj, Jeremie |
author_facet | Marc, Aurélien Kerioui, Marion Blanquart, François Bertrand, Julie Mitjà, Oriol Corbacho-Monné, Marc Marks, Michael Guedj, Jeremie |
author_sort | Marc, Aurélien |
collection | PubMed |
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 10(10) 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 | Online Article Text |
id | pubmed-8476126 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-84761262021-09-29 Quantifying the relationship between SARS-CoV-2 viral load and infectiousness Marc, Aurélien Kerioui, Marion Blanquart, François Bertrand, Julie Mitjà, Oriol Corbacho-Monné, Marc Marks, Michael Guedj, Jeremie eLife Microbiology and Infectious Disease 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(10) 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. eLife Sciences Publications, Ltd 2021-09-27 /pmc/articles/PMC8476126/ /pubmed/34569939 http://dx.doi.org/10.7554/eLife.69302 Text en © 2021, Marc et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Microbiology and Infectious Disease Marc, Aurélien Kerioui, Marion Blanquart, François Bertrand, Julie Mitjà, Oriol Corbacho-Monné, Marc Marks, Michael Guedj, Jeremie Quantifying the relationship between SARS-CoV-2 viral load and infectiousness |
title | 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_short | Quantifying the relationship between SARS-CoV-2 viral load and infectiousness |
title_sort | quantifying the relationship between sars-cov-2 viral load and infectiousness |
topic | Microbiology and Infectious Disease |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8476126/ https://www.ncbi.nlm.nih.gov/pubmed/34569939 http://dx.doi.org/10.7554/eLife.69302 |
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