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Stochasticity generates an evolutionary instability for infectious disease

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Read, Jonathan M. and Keeling, Matthew James (2007) Stochasticity generates an evolutionary instability for infectious disease. Ecology Letters, Vol.10 (No.9). pp. 818-827. ISSN 1461-023X

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Official URL: http://dx.doi.org/10.1111/j.1461-0248.2007.01078.x

Abstract

Traditional models of disease evolution are based upon the deterministic competition between strains that confer complete cross-immunity, and predict the selection of strains with higher basic reproductive ratios (R-0). In contrast, evolution in a stochastic setting is determined by a complex mixture of influences. Here, to isolate the impact of stochasticity, we constrain all competing strains to have an equal basic reproductive ratio - thereby eliminating deterministic selection. The resulting stochastic models predict an evolutionary unstable strategy, which separates a region favouring the evolution of rapid-transmission (acute) strains from one favouring persistent (chronic) strains. We find this to be a generic phenomenon with strain evolution consistently driven towards extremes of epidemiological behaviour. Even in the absence of an equal R-0 constraint, such stochastic selective pressures operate in addition to standard deterministic selection and will therefore influence the evolutionary behaviour of disease in an scenarios.

Item Type: Journal Item
Subjects: Q Science > QH Natural history > QH301 Biology
Divisions: Faculty of Science > Life Sciences (2010- ) > Biological Sciences ( -2010)
Faculty of Science > Mathematics
Journal or Publication Title: Ecology Letters
Publisher: Wiley-Blackwell Publishing Ltd.
ISSN: 1461-023X
Date: September 2007
Volume: Vol.10
Number: No.9
Number of Pages: 10
Page Range: pp. 818-827
Identification Number: 10.1111/j.1461-0248.2007.01078.x
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
URI: http://wrap.warwick.ac.uk/id/eprint/31377

Data sourced from Thomson Reuters' Web of Knowledge

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