Modelling the spread of diseases in clustered networks

Chai Molina, Lewi Stone*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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 R0 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.

Original languageEnglish
Pages (from-to)110-118
Number of pages9
JournalJournal of Theoretical Biology
StatePublished - 21 Dec 2012


  • Epidemic dynamics
  • Reproductive number
  • Transmissibility


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