A dimensionless number for understanding the evolutionary dynamics of antigenically variable RNA viruses.
Abstract
Antigenically variable RNA viruses are significant contributors to the burden of infectious
disease worldwide. One reason for their ubiquity is their ability to escape herd immunity
through rapid antigenic evolution and thereby to reinfect previously infected hosts.
However, the ways in which these viruses evolve antigenically are highly diverse.
Some have only limited diversity in the long-run, with every emergence of a new antigenic
variant coupled with a replacement of the older variant. Other viruses rapidly accumulate
antigenic diversity over time. Others still exhibit dynamics that can be considered
evolutionary intermediates between these two extremes. Here, we present a theoretical
framework that aims to understand these differences in evolutionary patterns by considering
a virus's epidemiological dynamics in a given host population. Our framework, based
on a dimensionless number, probabilistically anticipates patterns of viral antigenic
diversification and thereby quantifies a virus's evolutionary potential. It is therefore
similar in spirit to the basic reproduction number, the well-known dimensionless number
which quantifies a pathogen's reproductive potential. We further outline how our theoretical
framework can be applied to empirical viral systems, using influenza A/H3N2 as a case
study. We end with predictions of our framework and work that remains to be done to
further integrate viral evolutionary dynamics with disease ecology.
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https://hdl.handle.net/10161/9525Published Version (Please cite this version)
10.1098/rspb.2011.0435Publication Info
Koelle, Katia; Ratmann, Oliver; Rasmussen, David A; Pasour, Virginia; & Mattingly,
Jonathan (2011). A dimensionless number for understanding the evolutionary dynamics of antigenically
variable RNA viruses. Proc Biol Sci, 278(1725). pp. 3723-3730. 10.1098/rspb.2011.0435. Retrieved from https://hdl.handle.net/10161/9525.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Katharina V. Koelle
Associate Professor in the Department of Biology
My research focuses on the ecology and evolution of infectious diseases. I use a combination
of mathematical and statistical approaches to understand the processes driving the
disease dynamics of pathogens. My interests include developing models to improve our
understanding of how immune escape and other viral phenotypes impact the ecological
dynamics of RNA viruses, and, in turn, how these ecological dynamics create selection
pressures on viral pathogens. Additional interests include developing
This author no longer has a Scholars@Duke profile, so the information shown here reflects
their Duke status at the time this item was deposited.
Jonathan Christopher Mattingly
Kimberly J. Jenkins Distinguished University Professor of New Technologies
Jonathan Christopher Mattingly grew up in Charlotte, NC where he attended Irwin Ave
elementary and Charlotte Country Day. He graduated from the NC School of Science
and Mathematics and received a BS is Applied Mathematics with a concentration in physics
from Yale University. After two years abroad with a year spent at ENS Lyon studying
nonlinear and statistical physics on a Rotary Fellowship, he returned to the US to
attend Princeton University where he obtained a PhD in Applied and
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