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Selective sweeps in SARS-CoV-2 variant competition
The main mathematical result in this paper is that change of variables in the ordinary differential equation (ODE) for the competition of two infections in a Susceptible–Infected–Removed (SIR) model shows that the fraction of cases due to the new variant satisfies the logistic differential equation,...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9704709/ https://www.ncbi.nlm.nih.gov/pubmed/36383746 http://dx.doi.org/10.1073/pnas.2213879119 |
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author | Boyle, Laura Hletko, Sofia Huang, Jenny Lee, June Pallod, Gaurav Tung, Hwai-Ray Durrett, Richard |
author_facet | Boyle, Laura Hletko, Sofia Huang, Jenny Lee, June Pallod, Gaurav Tung, Hwai-Ray Durrett, Richard |
author_sort | Boyle, Laura |
collection | PubMed |
description | The main mathematical result in this paper is that change of variables in the ordinary differential equation (ODE) for the competition of two infections in a Susceptible–Infected–Removed (SIR) model shows that the fraction of cases due to the new variant satisfies the logistic differential equation, which models selective sweeps. Fitting the logistic to data from the Global Initiative on Sharing All Influenza Data (GISAID) shows that this correctly predicts the rapid turnover from one dominant variant to another. In addition, our fitting gives sensible estimates of the increase in infectivity. These arguments are applicable to any epidemic modeled by SIR equations. |
format | Online Article Text |
id | pubmed-9704709 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-97047092022-11-29 Selective sweeps in SARS-CoV-2 variant competition Boyle, Laura Hletko, Sofia Huang, Jenny Lee, June Pallod, Gaurav Tung, Hwai-Ray Durrett, Richard Proc Natl Acad Sci U S A Physical Sciences The main mathematical result in this paper is that change of variables in the ordinary differential equation (ODE) for the competition of two infections in a Susceptible–Infected–Removed (SIR) model shows that the fraction of cases due to the new variant satisfies the logistic differential equation, which models selective sweeps. Fitting the logistic to data from the Global Initiative on Sharing All Influenza Data (GISAID) shows that this correctly predicts the rapid turnover from one dominant variant to another. In addition, our fitting gives sensible estimates of the increase in infectivity. These arguments are applicable to any epidemic modeled by SIR equations. National Academy of Sciences 2022-11-03 2022-11-22 /pmc/articles/PMC9704709/ /pubmed/36383746 http://dx.doi.org/10.1073/pnas.2213879119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Physical Sciences Boyle, Laura Hletko, Sofia Huang, Jenny Lee, June Pallod, Gaurav Tung, Hwai-Ray Durrett, Richard Selective sweeps in SARS-CoV-2 variant competition |
title | Selective sweeps in SARS-CoV-2 variant competition |
title_full | Selective sweeps in SARS-CoV-2 variant competition |
title_fullStr | Selective sweeps in SARS-CoV-2 variant competition |
title_full_unstemmed | Selective sweeps in SARS-CoV-2 variant competition |
title_short | Selective sweeps in SARS-CoV-2 variant competition |
title_sort | selective sweeps in sars-cov-2 variant competition |
topic | Physical Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9704709/ https://www.ncbi.nlm.nih.gov/pubmed/36383746 http://dx.doi.org/10.1073/pnas.2213879119 |
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