Integrating Stochasticity And Network Structure Into An Epidemic Model

This paper brings together two important facets of disease transmission -- the effects of contact networks and the effects of chance. Using two well established approximation techniques we have been able to assess the expected size of variability due to the chance nature of transmission and recovery in both random-mixing models and network models.


We have shown that if these two models are forced to predict the same mean dynamics, then in general they predict very similar levels of variability; the only exception is when the prevalence of infection is very low.

We believe that the techniques we have adopted here can be extended to understand the dynamics and variability of epidemics spread through a range of more realistic contact networks.


Journal of the Royal Society Interface


Journal of the Royal Society Interface is the Society's cross-disciplinary publication promoting research at the interface between the physical and life sciences. It offers rapidity, visibility and high-quality peer review and is ranked fifth in JCR's multidisciplinary category. The journal also incorporates Interface Focus, a peer-reviewed, themed supplement, each issue of which concentrates on a specific cross-disciplinary subject.


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