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The importance of the generation interval in investigating dynamics and control of new SARS-CoV-2 variants
Inferring the relative strength (i.e. the ratio of reproduction numbers) and relative speed (i.e. the difference between growth rates) of new SARS-CoV-2 variants is critical to predicting and controlling the course of the current pandemic. Analyses of new variants have primarily focused on character...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9198506/ https://www.ncbi.nlm.nih.gov/pubmed/35702867 http://dx.doi.org/10.1098/rsif.2022.0173 |
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author | Park, Sang Woo Bolker, Benjamin M. Funk, Sebastian Metcalf, C. Jessica E. Weitz, Joshua S. Grenfell, Bryan T. Dushoff, Jonathan |
author_facet | Park, Sang Woo Bolker, Benjamin M. Funk, Sebastian Metcalf, C. Jessica E. Weitz, Joshua S. Grenfell, Bryan T. Dushoff, Jonathan |
author_sort | Park, Sang Woo |
collection | PubMed |
description | Inferring the relative strength (i.e. the ratio of reproduction numbers) and relative speed (i.e. the difference between growth rates) of new SARS-CoV-2 variants is critical to predicting and controlling the course of the current pandemic. Analyses of new variants have primarily focused on characterizing changes in the proportion of new variants, implicitly or explicitly assuming that the relative speed remains fixed over the course of an invasion. We use a generation-interval-based framework to challenge this assumption and illustrate how relative strength and speed change over time under two idealized interventions: a constant-strength intervention like idealized vaccination or social distancing, which reduces transmission rates by a constant proportion, and a constant-speed intervention like idealized contact tracing, which isolates infected individuals at a constant rate. In general, constant-strength interventions change the relative speed of a new variant, while constant-speed interventions change its relative strength. Differences in the generation-interval distributions between variants can exaggerate these changes and modify the effectiveness of interventions. Finally, neglecting differences in generation-interval distributions can bias estimates of relative strength. |
format | Online Article Text |
id | pubmed-9198506 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-91985062022-06-15 The importance of the generation interval in investigating dynamics and control of new SARS-CoV-2 variants Park, Sang Woo Bolker, Benjamin M. Funk, Sebastian Metcalf, C. Jessica E. Weitz, Joshua S. Grenfell, Bryan T. Dushoff, Jonathan J R Soc Interface Life Sciences–Mathematics interface Inferring the relative strength (i.e. the ratio of reproduction numbers) and relative speed (i.e. the difference between growth rates) of new SARS-CoV-2 variants is critical to predicting and controlling the course of the current pandemic. Analyses of new variants have primarily focused on characterizing changes in the proportion of new variants, implicitly or explicitly assuming that the relative speed remains fixed over the course of an invasion. We use a generation-interval-based framework to challenge this assumption and illustrate how relative strength and speed change over time under two idealized interventions: a constant-strength intervention like idealized vaccination or social distancing, which reduces transmission rates by a constant proportion, and a constant-speed intervention like idealized contact tracing, which isolates infected individuals at a constant rate. In general, constant-strength interventions change the relative speed of a new variant, while constant-speed interventions change its relative strength. Differences in the generation-interval distributions between variants can exaggerate these changes and modify the effectiveness of interventions. Finally, neglecting differences in generation-interval distributions can bias estimates of relative strength. The Royal Society 2022-06-15 /pmc/articles/PMC9198506/ /pubmed/35702867 http://dx.doi.org/10.1098/rsif.2022.0173 Text en © 2022 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Life Sciences–Mathematics interface Park, Sang Woo Bolker, Benjamin M. Funk, Sebastian Metcalf, C. Jessica E. Weitz, Joshua S. Grenfell, Bryan T. Dushoff, Jonathan The importance of the generation interval in investigating dynamics and control of new SARS-CoV-2 variants |
title | The importance of the generation interval in investigating dynamics and control of new SARS-CoV-2 variants |
title_full | The importance of the generation interval in investigating dynamics and control of new SARS-CoV-2 variants |
title_fullStr | The importance of the generation interval in investigating dynamics and control of new SARS-CoV-2 variants |
title_full_unstemmed | The importance of the generation interval in investigating dynamics and control of new SARS-CoV-2 variants |
title_short | The importance of the generation interval in investigating dynamics and control of new SARS-CoV-2 variants |
title_sort | importance of the generation interval in investigating dynamics and control of new sars-cov-2 variants |
topic | Life Sciences–Mathematics interface |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9198506/ https://www.ncbi.nlm.nih.gov/pubmed/35702867 http://dx.doi.org/10.1098/rsif.2022.0173 |
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