Modelling Infection Dynamics and Evolution of Viruses in Plant Populations

Abstract

Mathematical models have been used extensively to analyse and/or predict the dynamics of pathogen infection in host populations, as well as the evolution of key pathogen traits, notably infectivity and virulence. Model analyses have been very useful in identifying factors that affect infection dynamics and pathogen evolution, and in predicting their effects under different scenarios. However, a serious shortcoming of theoretical analyses is that often there is not enough information on how realistic the underlying assumptions are, and very often there is a serious lack of information on the range of values of key model parameters. An example is the classical susceptible-infected-recovered (SIR) model, first proposed by Kermack and McKendrick [8] in 1927, and becoming the basis to predict virulence evolution. A central assumption of this model is that both virulence, defined as the effect of infection on host mortality, and the rate of transmission to new hosts, are positively correlated with the within-host multiplication rate of the pathogen, so that a trade-off between virulence and transmission is established to optimize the intrinsic reproduction value. Interestingly, a positive correlation between virulence and within-host multiplication has been demonstrated in few host-parasite systems, and seems not to be the rule for the whole classes of parasites, including plant viruses [10], which has not discouraged the use (and the utility) of SIR-based evolutionary models.