UBC Research Data

On the evolutionary epidemiology of SARS-CoV-2 Day, Troy; Gandon, Sylvain; Lion, Sébastien; Otto, Sarah P.

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Abstract

There is no doubt that the novel coronavirus SARS-CoV-2 that causes COVID-19 is mutating and thus has the potential to adapt during the current pandemic. Whether this evolution will lead to changes in the transmission, the duration, or the severity of the disease is not clear. This has led to considerable scientific and media debate, from raising alarms about evolutionary change to dismissing it. Here we review what little is currently known about the evolution of SARS-CoV-2 and extend existing evolutionary theory to consider how this disease might evolve during the COVID-19 pandemic. While there is currently no definitive evidence that SARS-CoV-2 is undergoing further adaptation, continued, evidence-based, analysis of evolutionary change is important so that public health measures can be adjusted in response to substantive changes in the infectivity or severity of COVID-19.; Methods

The dataset is a supplementary Mathematica package that derives the analytical results and simulates the dynamics, as illustrated in Figures 3-4. Additional supplementary figures explore the robustness of the results to alternative parameter choices.; Usage notes

The source notebook was written in Mathematica 8 (Wolfram Research Inc.) and is provided in .nb (Mathematica) and PDF formats.

Item Metadata

Title	On the evolutionary epidemiology of SARS-CoV-2
Creator	Day, Troy; Gandon, Sylvain; Lion, Sébastien; Otto, Sarah P.
Date Issued	2021-05-19
Description	<b>Abstract</b><br/> <span><span style="font-style:normal;"><span><span style="font-weight:normal;"><span style="letter-spacing:normal;"><span><span><span style="white-space:normal;"><span><span><span>There is no doubt that the novel coronavirus SARS-CoV-2 that causes COVID-19 is mutating and thus has the potential to adapt during the current pandemic. Whether this evolution will lead to changes in the transmission, the duration, or the severity of the disease is not clear. This has led to considerable scientific and media debate, from raising alarms about evolutionary change to dismissing it. Here we review what little is currently known about the evolution of SARS-CoV-2 and extend existing evolutionary theory to consider how this disease might evolve during the COVID-19 pandemic. While there is currently no definitive evidence that SARS-CoV-2 is undergoing further adaptation, continued, evidence-based, analysis of evolutionary change is important so that public health measures can be adjusted in response to substantive changes in the infectivity or severity of COVID-19.</span></span></span></span></span></span></span></span></span></span></span></p>; <b>Methods</b><br /> The dataset is a supplementary <em>Mathematica</em> package that derives the analytical results and simulates the dynamics, as illustrated in Figures 3-4. Additional supplementary figures explore the robustness of the results to alternative parameter choices.</p>; <b>Usage notes</b><br /> The source notebook was written in <em>Mathematica</em> 8 (Wolfram Research Inc.) and is provided in .nb (<em>Mathematica</em>) and PDF formats.</p>
Subject	Other; Viral evolution; Disease epidemiology; evolutionary model
Type	Dataset
Notes	Dryad version number: 5</p> Version status: submitted</p> Dryad curation status: Published</p> Sharing link: https://datadryad.org/stash/share/ibLW-Sd5crZam-K7HmTL6Qc3B0toVqewyAEUopJ9oNs</p> Storage size: 59850143</p> Visibility: public</p>
Date Available	2020-07-01
Provider	University of British Columbia Library
License	This dataset is made available under a Creative Commons CC0 license with the following additional/modified terms and conditions: CC0 Waiver
DOI	10.14288/1.0397965
URI	https://doi.org/10.5683/SP2/VKH3LE
Publisher DOI	https://doi.org/10.5683/SP2/VKH3LE; https://doi.org/10.5061/dryad.5hqbzkh3g
Grant Funding Agency	Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche; Agence Nationale de la Recherche
Rights URI	https://creativecommons.org/publicdomain/zero/1.0/
Aggregated Source Repository	Dataverse

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This dataset is made available under a Creative Commons CC0 license with the following additional/modified terms and conditions: CC0 Waiver

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