Catalysis Meeting

Evolution of infectious diseases: integrating empirical and modelling approaches

PI(s): Sarah Reece (Institutes of Evolution, Immunology and Infection Research)
Andrew Read (Pennsylvania State University)
Nicole Mideo (University of Edinburgh)
Nick Savill (University of Edinburgh)
Start Date: 1-May-2010
End Date: 30-Apr-2011
Keywords:
Using an evolutionary framework to understand the biology of infectious diseases is an emerging interdisciplinary field with important implications for evolutionary biology and biomedicine [1-5].
For evolutionary biology, parasites present a novel and independent test for the explanatory power and generality of an approach that has been largely developed to explain the biology of traditionally studied multi-cellular taxa . Whilst reductionist biomedicine reveals the proximate mechanisms responsible for disease, the selective forces that shape parasite traits (e.g. virulence) and their within-host dynamics remain poorly understood. Yet, unravelling the ecological and evolutionary explanations for disease is central to predicting how parasites will adapt in response to interventions, such as drugs and vaccines [e.g. 6].

Whilst numerous mathematical models of disease processes exist, they are derived in isolation from data. High quality data sets from experimental manipulations of disease model systems are rapidly accumulating and can be used to develop and test models of the ecological processes that underlie evolution at the within- and between-host scales. Such collaboration between modellers and empiricists has been constrained by a lack of communication between these disciplines. However, we have recently demonstrated that iterating model building and empirical testing is mutually beneficial and the most powerful way to progress [e.g. 7-12]. We will develop this community by bringing together modellers and empiricists with common interests in disease evolution. Our primary aims are to identify key questions and coordinate integrative research that will provide novel insights that could not be gained by either approach alone.

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