title: Modelling the spread of diseases in clustered networks.
abstract: It is now well appreciated that population structure can have a major impact on disease dynamics, outbreak sizes and epidemic thresholds. Indeed, on some networks, epidemics occur only for sufficiently high transmissibility, whereas in others (e.g. scale-free networks), no such threshold effect exists. While the effects of variability in connectivity are relatively well known, the effects of clustering in the population on disease dynamics are still debated. We develop a simple and intuitive model for calculating the reproductive number R(0) on clustered networks with arbitrary degree distribution. The model clearly shows that in general, clustering impedes epidemic spread; however, its effects are usually small and/or coupled with other topological properties of the network. The model is generalized to take into account degree-dependent transmissibility (e.g., relevant for disease vectors). The model is also used to easily rederive a known result concerning the formation of the giant component.
authors.affiliation: Biomathematics Unit, Department of Zoology, Faculty of Life Sciences, Tel Aviv University, Israel. chai.molina@gmail.com
authors.forename: Chai
authors.initials: C
authors.lastname: Molina
authors.forename: Lewi
authors.initials: L
authors.lastname: Stone
mesh_terms: D016000:Cluster Analysis; D004198:Disease Susceptibility; D018562:Disease Transmission, Infectious; D006801:Humans; D008954:Models, Biological; D011336:Probability