Simulating individual-based models of epidemics in hierarchical networks

Rick Quax, David A. Bader, Peter M.A. Sloot

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


Current mathematical modeling methods for the spreading of infectious diseases are too simplified and do not scale well. We present the Simulator of Epidemic Evolution in Complex Networks (SEECN), an efficient simulator of detailed individual-based models by parameterizing separate dynamics operators, which are iteratively applied to the contact network. We reduce the network generator's computational complexity, improve cache efficiency and parallelize the simulator. To evaluate its running time we experiment with an HIV epidemic model that incorporates up to one million homosexual men in a scale-free network, including hierarchical community structure, social dynamics and multi-stage intranode progression. We find that the running times are feasible, on the order of minutes, and argue that SEECN can be used to study realistic epidemics and its properties experimentally, in contrast to defining and solving ever more complicated mathematical models as is the current practice.

Original languageEnglish (US)
Title of host publicationComputational Science - ICCS 2009 - 9th International Conference, Proceedings
Number of pages10
EditionPART 1
StatePublished - 2009
Externally publishedYes
Event9th International Conference on Computational Science, ICCS 2009 - Baton Rouge, LA, United States
Duration: May 25 2009May 27 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5544 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other9th International Conference on Computational Science, ICCS 2009
Country/TerritoryUnited States
CityBaton Rouge, LA

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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