The strength of connection between cities may be density independent, that is, the sum of connectivity of a city to all its neighbours does not depend on the number of neighbours that city has. In contrast, density-dependent connectivity links two cities at a strength solely determined by the sizes of those cities and their distance apart, so that the total connectivity of any one city scales with the number of close neighbours. Density-independent transmission gives a total force of infection, which is independent of the remoteness of the population, whereas density-dependent transmission will cause populations with many neighbours to experience a higher force of infection than those cities that have few neighbours. Thus, a densitydependent model will predict that isolated populations are less likely to become infected than populations with many neighbours, or few very large neighbours. The concepts of density dependence/independence have not only been used to model interactions between cities; they have also been used extensively in individual based models of disease spread. Most past studies tend to assume either density dependence (e.g. for animal epidemics; [19, 20] ), or density independence (e.g. for most human diseases) [3, 4] . Here, we explore the extent to which city-to-city (rather than individualto-individual) contacts are density independent by constructing a model that can capture intermediate levels of density dependence.