We obtained United Nations Food and Agriculture Organization data on trade in Live Swine (commodity code HS96:S0103) and Live Poultry (S0105) from the U.N. Comtrade data portal [14] . We analyzed data from the last ten years (the approximate time since 2009 A/H1N1 diverged from the nearest sampled virus) [7] , and focused on trade to North America (Mexico, Canada and United States) from outside this region, as well as trade to Mexico within the North American region. Figure S1 Model predictions compared with actual case arrival dates. Dates of case arrivals (black diamonds) for cases that were reported before our cut off of May 8th. Grey whisker plots represent 95% confidence intervals for predicted arrival date, with interior grey bar as expected (mean) date of arrival from survival analysis. Found at: doi:10.1371/journal.pone.0012763.s001 (0.02 MB PDF) Figure S2 Forward prediction of future case arrival dates. Dates of case arrivals (black diamonds) for cases that were reported after our cut off of May 8th, but before May 19th. Grey whisker plots represent 95% confidence intervals for predicted arrival date, with interior grey bar as expected (mean) date of arrival from survival analysis. Found at: doi:10.1371/journal.pone.0012763.s002 (0.02 MB PDF) Figure S3 Forward prediction of future case arrival dates. Grey whisker plots represent 95% confidence intervals for predicted arrival date, with interior grey bar as expected (mean) date of arrival from survival analysis. Found at: doi:10.1371/journal.pone.0012763.s003 (0.03 MB PDF) Evolutionary Entropy Determines Invasion Success in Emergent Epidemics BACKGROUND: Standard epidemiological theory claims that in structured populations competition between multiple pathogen strains is a deterministic process which is mediated by the basic reproduction number ([Image: see text]) of the individual strains. A new theory based on analysis, simulation and empirical study challenges this predictor of success. PRINCIPAL FINDINGS: We show that the quantity [Image: see text] is a valid predictor in structured populations only when size is infinite. In this article we show that when population size is finite the dynamics of infection by multi-strain pathogens is a stochastic process whose outcome can be predicted by evolutionary entropy, S, an information theoretic measure which describes the uncertainty in the infectious age of an infected parent of a randomly chosen new infective. Evolutionary entropy characterises the demographic stability or robustness of the population of infectives. This statistical parameter determines the duration of infection and thus provides a quantitative index of the pathogenicity of a strain. Standard epidemiological theory based on [Image: see text] as a measure of selective advantage is the limit as the population size tends to infinity of the entropic selection theory. The standard model is an approximation to the entropic selection theory whose validity increases with population size. CONCLUSION: An epidemiological analysis based on entropy is shown to explain empirical observations regarding the emergence of less pathogenic strains of human influenza during the antigenic drift phase. Furthermore, we exploit the entropy perspective to discuss certain epidemiological patterns of the current H1N1 swine 'flu outbreak. Recent years have seen an apparent acceleration in the rate of emergence of new infectious disease pathogens in the human population [1] . Some of these have their origins in animal (wild or domesticated) reservoirs [2] [3] [4] , and the years since 2003 have witnessed the appearance of SARS [5, 6] and swine flu [7] . The 20 th century saw, for example, the emergence of pandemic 'flu in 1918, 1957 and 1968 (with a limited H1N1 re-emergent outbreak in 1977) [8] , avian 'flu [9] and the rise of HIV in the 1980's [10, 11] . Additionally, antibiotic-resistant pathogens have become increasingly widespread in the past decade, particularly in healthcare settings [12] . Antigenically-variable pathogens are responsible for much of the burden of communicable disease in the world today. Therefore, developing an understanding of the factors that lead to the emergence and spread of novel pathogenic agents and strains is a topic of great interest. In recent months the emergence of a swine 'flu (H1N1 2009) with human-to-human transmission capability has re-focussed attention on this issue [7, 13] . Likewise, studies, such of those of Creanza et al. [14] who used a computational analysis of viral nucleotide and amino acid sequence data collected during seasonal 'flu epidemics show how diversity declines over the course of an epidemic. These observations underscore the role that ecological constraint play in the evolution of pathogens.