2019-EEID US-UK Heterogeneities, Diversity and the Evolution of Infectious Disease

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Infectious disease transmission within populations rarely approximates as a homogenous, random "well mixed" process. Individual hosts vary in their susceptibility and transmissibility through genetic and epigenetic effects, their condition and their immune memory. In addition, variation in disease contacts is typical within populations due to how individuals are arranged in space, how they move and how they interact socially generating population structure even in the absence of heterogeneities in the environment. These individual heterogeneities and the heterogeneity in transmission due to population structure interact with variation in specificity between host genotypes and parasites strains in most if not all systems. We have an incomplete theory on what each of these three sources of heterogeneities - individual, population and interaction - have on the epidemiology of disease. For example, the role of 'superspreaders' in the SARS is a classic example of the importance of heterogeneity in disease contacts to epidemic outcomes. Furthermore, we have relatively little understanding of the implications of such heterogeneity to the evolution of infectious disease beyond theory and limited experimental tests on the role of regular spatial structure. In particular, how different heterogeneities interact to determine the evolution of disease virulence and host defense is little studied. New theory is therefore required to test their implications to the long-term evolutionary outcomes, but perhaps more importantly we need to understand transient short-term responses. The key intellectual challenges that this proposal will address are to (1) extend existing theory to understand the impact of population and individual level heterogeneities and their interaction on the evolution of host and parasite traits, (2) develop new theoretical methods to predict the transient evolutionary behavior, (3) test these predictions in a tractable laboratory model system and (4) apply the theory to agricultural systems to understand the role of agri-evolutionary feedbacks and management imposed heterogeneities on the evolution infectious disease.