Scalable, efficient epidemiological simulation

  • Authors:
  • Stephen Eubank

  • Affiliations:
  • D-2, MS-M997, Los Alamos National Laboratory, Los Alamos, NM

  • Venue:
  • Proceedings of the 2002 ACM symposium on Applied computing
  • Year:
  • 2002

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Abstract

We describe the design and implementation of a system for simulating the spread of disease among individuals in a large urban population over the course of several weeks. In contrast to traditional approaches, we do not assume uniform mixing among large sub-populations or split the population into spatial or demographic subpopulations determined a priori. Instead, we rely on empirical estimates of the social network, or contact patterns, that are produced by TRANSIMS, a large-scale simulation of transportation systems.