Foot-and-mouth is one of the world's most economically important livestock diseases. We developed an individual farm-based stochastic model of the current UK epidemic. The fine grain of the epidemiological data reveals the infection dynamics at an unusually high spatiotemporal resolution. We show that the spatial distribution, size, and species composition of farms all influence the observed pattern and regional variability of outbreaks. The other key dynamical component is long-tailed stochastic dispersal of infection, combining frequent local movements with occasional long jumps. We assess the history and possible duration of the epidemic, the performance of control strategies, and general implications for disease dynamics in space and time.

SUMMARYIn this paper we review the published literature on patterns of abundance and aggregation of macroparasites in wildlife host populations. We base this survey on quantitative analyses of mean burden and a number of measures of the degree of aggregation of parasite burdens between hosts. All major parasite and vertebrate host taxa were represented in the database. Mean parasite burden was found to be log-normally distributed, indicating that all parasite burdens are regulated to some degree. In addition, all but one of the parasitic infections were aggregated with respect to their hosts, and the relationship between log mean parasite burden and log variance was found to be very strong (R2= 0·87). That is, for a given mean parasite burden there are constraints on the degree of variation in individual host burdens. The aggregated nature of the parasitic infections is also apparent from other measures of the degree of aggregation: prevalence – mean relationships, and the negative binomial parameter,k. Using a relatively new technique for parasitological infection data – tree-based models, as well as traditional linear models – a number of the parasitic infections was found to be associated with systematically lower or higher parasite burdens. Possible biological explanations for these and other patterns are proposed.

Frequency distributions from 49 published wildlife host-macroparasite systems were analysed by maximum likelihood for goodness of fit to the negative binomial distribution. In 45 of the 49 (90%) data-sets, the negative binomial distribution provided a statistically satisfactory fit. In the other 4 data-sets the negative binomial distribution still provided a better fit than the Poisson distribution, and only 1 of the data-sets fitted the Poisson distribution. The degree of aggregation was large, with 43 of the 49 data-sets having an estimated k of less than 1. From these 49 data-sets, 22 subsets of host data were available (i.e. host data could be divided by either host sex, age, where or when hosts were sampled). In 11 of these 22 subsets there was significant variation in the degree of aggregation between host subsets of the same host-parasite system. A common k estimate was always larger than that obtained with all the host data considered together. These results indicate that lumping host data can hide important variations in aggregation between hosts and can exaggerate the true degree of aggregation. Wherever possible common k estimates should be used to estimate the degree of aggregation. In addition, significant differences in the degree of aggregation between subgroups of host data, were generally associated with significant differences in both mean parasite burdens and the prevalence of infection.

Foot-and-mouth disease (FMD) in the UK provides an ideal opportunity to explore optimal control measures for an infectious disease. The presence of fine-scale spatio-temporal data for the 2001 epidemic has allowed the development of epidemiological models that are more accurate than those generally created for other epidemics and provide the opportunity to explore a variety of alternative control measures. Vaccination was not used during the 2001 epidemic; however, the recent DEFRA (Department for Environment Food and Rural Affairs) contingency plan details how reactive vaccination would be considered in future. Here, using the data from the 2001 epidemic, we consider the optimal deployment of limited vaccination capacity in a complex heterogeneous environment. We use a model of FMD spread to investigate the optimal deployment of reactive ring vaccination of cattle constrained by logistical resources. The predicted optimal ring size is highly dependent upon logistical constraints but is more robust to epidemiological parameters. Other ways of targeting reactive vaccination can significantly reduce the epidemic size; in particular, ignoring the order in which infections are reported and vaccinating those farms closest to any previously reported case can substantially reduce the epidemic. This strategy has the advantage that it rapidly targets new foci of infection and that determining an optimal ring size is unnecessary.

Identification of the relative importance of within-and betweenhost variability in infectiousness and the impact of these heterogeneities on the transmission dynamics of infectious agents can enable efficient targeting of control measures. Cattle, a major reservoir host for the zoonotic pathogen Escherichia coli O157, are known to exhibit a high degree of heterogeneity in bacterial shedding densities. By relating bacterial count to infectiousness and fitting dynamic epidemiological models to prevalence data from a cross-sectional survey of cattle farms in Scotland, we identify a robust pattern: Ϸ80% of the transmission arises from the 20% most infectious individuals. We examine potential control options under a range of assumptions about within-and betweenhost variability in infection dynamics. Our results show that the within-herd basic reproduction ratio, R 0, could be reduced to <1 with targeted measures aimed at preventing infection in the 5% of individuals with the highest overall infectiousness. Alternatively, interventions such as vaccination or the use of probiotics that aim to reduce bacterial carriage could produce dramatic reductions in R 0 by preventing carriage at concentrations corresponding to the top few percent of the observed range of counts. We conclude that a greater understanding of the cause of the heterogeneity in bacterial carriage could lead to highly efficient control measures to reduce the prevalence of E. coli O157.bacterial count ͉ core groups ͉ super shedder ͉ superspreading ͉ targeted control T he role of heterogeneous infectiousness on the course of disease outbreaks was highlighted during the recent severe acute respiratory syndrome outbreak (1), in which a few individuals were responsible for a disproportionate number of transmission events. Awareness of heterogeneities in transmission dynamics can be important for the effective implementation of disease control measures and can lead to efficient targeting of interventions at a subset of the population (2-5). Factors that might lead to such heterogeneities include variability in infectiousness, exposure, genetic susceptibility, contact rates, and behavior (6-10). Quantifying their impact on the transmission dynamics can be achieved through direct methods, such as contact tracing and outbreak reconstruction (1, 11), or indirectly through their effect on the distribution of infected cases (12).Escherichia coli O157 is an important zoonosis with a known reservoir in cattle (13,14). Prevalences of infection are generally low, usually reported to be Ͻ10% of animals carrying the pathogen (14). Typically, however, the distribution of prevalences is highly skewed (15); at any one time, shedding is not detected in the majority of cattle groups, but a small proportion of groups contains high numbers of individuals shedding bacteria in their feces.The range of prevalences of an infectious agent in a small population is expected to be influenced both by stochasticity and underlying heterogeneities in the transmission dynamics. In a recent a...