Antigentic Drift: Ww0. Recent work on the genetic and antigenic evolution of Influenza A H3N2 in humans has demonstrated that seasonal 'flu epidemics emerge from seed strains originating in countries of south-east Asia which subsequently spread sequentially through the global population [32] [33] [34] [35] . This suggests that novel H3N2 variants compete with existing strains within the E-SE Asia circulation network with the dominant strain being responsible for generating the next global seasonal 'flu strain. Once out of the seeding region there appears to be little subsequent viral evolution [32] , though as pointed out by Rambaut et al. [36] subsequent changes tend to be deleterious and so die out. When a new H3N2 variant is generated within the seeding region it competes for susceptibles with existing variants. The epidemiological picture in this densely populated SE-Asia seeding region is one of strong fluctuations of multiple circulating strains [32] . Much of this fluctuation is driven by the cross-reactive immunity and heterogeneity of host population immune response to the different strains and finite size population effects. The dynamics are characterised by repeated boom-bust cycles in the strain populations, so competition is taking place between a new variant and a rapidly growing incumbent pathogen population that has a large positive growth rate r, implying that the reproductive potential Ww0. Information on the infectious netreproductive function from which we would infer the value of c is less readily available [33] . It is plausible to assume, however, that the rate at which secondary infections are produced is broadly correlated with pathogen burden. This results in a netreproductive function for influenza [33, Figure 1 ] that is slightly skewed towards the early stages of host infection, implying that c is small and negative. From Table S1 , the constraints Ww0 and cv0 suggest that new variants will enjoy a selective advantage if their evolutionary entropy is lower than other competing strains (DSv0) during the competitive growth phase. In this model the invasion success of the new strain will be dependent on the relative evolutionary entropy of the variant contingent on the demographic variables W and c. The information given in Table  S1 can be invoked to determine the selective outcome of competing strains. This information underscores the difference between the deterministic process which defines the classical models and the stochastic process which characterises entropic epidemiology. A variant strain has epidemic potential and will dominate existing H3N2 strains providing that DSv0. By contrast, in a deterministic model (equation 2) the outcome of competition between strains is a deterministic process predicted wholly by R 0 -the strain with the largest basic reproduction number will always dominate. In the entropic model there is a probability of a downward drift in the evolutionary entropy, S, of the dominant strain. Within the classical framework (infinite population size) the outcome is deterministically ordained, that is, we expect that those variants which produce more secondary infectives to dominate all others. By contrast, in a finite population (and contingent on the values of W, and to a lesser extent c) the outcome has an intrinsic stochastic component: it is the evolutionary entropy that determines success so there may be dominant variants which produce fewer secondary infectives (i.e. have a lower growth rate and R 0 ) than their co-circulating competitors.