Susceptible-infected-recovered epidemics in dynamic contact networks.

ABSTRACT: Contact patterns in populations fundamentally influence the spread of infectious diseases. Current mathematical methods for epidemiological forecasting on networks largely assume that contacts between individuals are fixed, at least for the duration of an outbreak. In reality, contact patterns may be quite fluid, with individuals frequently making and breaking social or sexual relationships. Here, we develop a mathematical approach to predicting disease transmission on dynamic networks in which each individual has a characteristic behaviour (typical contact number), but the identities of their contacts change in time. We show that dynamic contact patterns shape epidemiological dynamics in ways that cannot be adequately captured in static network models or mass-action models. Our new model

SUBMITTER: Volz E 

PROVIDER: S-EPMC2291166 | biostudies-literature | 2007 Dec

REPOSITORIES: biostudies-literature