Beyond Population Averages: Incorporating Individual Variation into Models of Disease Invasion and Control
(James Lloyd-Smith, UC Berkeley)

It is common practice in disease modelling studies to characterize groups or subgroups using population-average parameters, most importantly the basic reproductive number, R0.  In this talk I will show evidence of significant individual-level variation in transmission patterns for many diseases, and discuss how this can be incorporated into epidemiological models.  I will introduce a natural generalization of R0: the 'individual reproductive number', which is the expected number of secondary cases caused by a given infected individual.  Individual reproductive numbers for a population are drawn from a continuous distribution with mean R0. Superspreading events correspond to extreme values from the upper tail of this distribution.  This conceptual framework is readily incorporated into a branching process model of disease invasion, revealing large impacts on invasion dynamics for empirically-observed levels of variation.  I will discuss implications for control programs, and outline challenges for future research.