What the reproductive number R0 can and cannot tell us about COVID-19 dynamics

Clara L. Shaw; David A. Kennedy

doi:10.1016/j.tpb.2020.12.003

What the reproductive number R₀ can and cannot tell us about COVID-19 dynamics

Clara L. Shaw, David A. Kennedy

Research output: Contribution to journal › Comment/debate › peer-review

21 Scopus citations

Abstract

The reproductive number R (or R₀, the initial reproductive number in an immune-naïve population) has long been successfully used to predict the likelihood of pathogen invasion, to gauge the potential severity of an epidemic, and to set policy around interventions. However, often ignored complexities have generated confusion around use of the metric. This is particularly apparent with the emergent pandemic virus SARS-CoV-2, the causative agent of COVID-19. We address some misconceptions about the predictive ability of the reproductive number, focusing on how it changes over time, varies over space, and relates to epidemic size by referencing the mathematical definition of R and examples from the current pandemic. We hope that a better appreciation of the uses, nuances, and limitations of R and R₀ facilitates a better understanding of epidemic spread, epidemic severity, and the effects of interventions in the context of SARS-CoV-2.

Original language	English (US)
Pages (from-to)	2-9
Number of pages	8
Journal	Theoretical Population Biology
Volume	137
DOIs	https://doi.org/10.1016/j.tpb.2020.12.003
State	Published - Feb 2021
Externally published	Yes

Bibliographical note

Funding Information:
We thank Amrita Bhattacharya and two anonymous reviewers for feedback on earlier versions of the text. This work was supported by startup funds from The Pennsylvania State University, United States. DAK was also partially supported by National Science Foundation, United States grant DEB-1754692. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Funding Information:
We thank Amrita Bhattacharya and two anonymous reviewers for feedback on earlier versions of the text. This work was supported by startup funds from The Pennsylvania State University, United States . DAK was also partially supported by National Science Foundation, United States grant DEB-1754692 . The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Publisher Copyright:
© 2021 Elsevier Inc.

Keywords

COVID-19
Epidemic size
Heterogeneity
Interventions
R
SARS-CoV-2

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.tpb.2020.12.003

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Cite this

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abstract = "The reproductive number R (or R0, the initial reproductive number in an immune-na{\"i}ve population) has long been successfully used to predict the likelihood of pathogen invasion, to gauge the potential severity of an epidemic, and to set policy around interventions. However, often ignored complexities have generated confusion around use of the metric. This is particularly apparent with the emergent pandemic virus SARS-CoV-2, the causative agent of COVID-19. We address some misconceptions about the predictive ability of the reproductive number, focusing on how it changes over time, varies over space, and relates to epidemic size by referencing the mathematical definition of R and examples from the current pandemic. We hope that a better appreciation of the uses, nuances, and limitations of R and R0 facilitates a better understanding of epidemic spread, epidemic severity, and the effects of interventions in the context of SARS-CoV-2.",

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