An epidemic model on the dispersal networks at population and individual levels

A network model at the population level and the individual level, which simulates both between-herd dynamics and within-herd dynamics, is formulated. We investigated effects of dispersal rates and local dynamics on the outcome of an epidemic at the population level. Numerical studies show that dispersal may strengthen spread of the disease on average, but lead to a less tendency for damped oscillation. Further, different types of clustering behaviors, from synchronized to completely desynchronized, are observed within our system. The results show that strengthening the coupling between farms via the immigration of infectives tends to enhance (in-phase) synchronization. Dynamic complexity, including chaotic, quasi-periodic or periodic behaviour, is observed in our model with varying the coupling strength. The main results help to explain differences in observed epidemiological patterns and to identify possible causes for different strains of Salmonella developing so much variation in their infection dynamics in UK dairy herds.