We develop a framework for simulating a realistic, evolving social network (a city) into which a disease is introduced. We compare our results to prevaccine era measles data for England and Wales, and find that they capture the quantitative and qualitative features of epidemics in populations spanning two orders of magnitude. Our results provide unique insight into how and why the social topology of the contact network influences the propagation of the disease through the population. We argue that network simulation is suitable for concurrently probing contact network dynamics and disease dynamics in ways that prior modeling approaches cannot and it can be extended to the study of less well-documented diseases.

Original languageEnglish (US)
Pages (from-to)2663-2674
Number of pages12
JournalPhysica A: Statistical Mechanics and its Applications
Issue number13
StatePublished - Jul 1 2010

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Condensed Matter Physics


Dive into the research topics of 'Disease dynamics in a dynamic social network'. Together they form a unique fingerprint.

Cite this