EpiSimsThe Epidemiological Simulation System (EpiSims) has been developed with support from the U.S. Departments of Energy, Homeland Security, and Health and Human Services, with the purpose of providing an experimental testbed for analyzing proposed responses to natural or intentionally caused disease outbreaks.
EpiSims models the spread of disease in urban areas, allowing for the assessment of prevention, intervention, and response strategies by simulating the daily movements of synthetic individuals within an urban region. EpiSims allows the user to specify the effects in detail of a pathogen on a specific person, and to assign different effects to various people based on demographic characteristics. In conjunction with population mobility models it can represent behavioral reactions to an outbreak, including official interventions.
EpiSims provides detailed information about every simulated person and the significant event that happens to each person during the simulation—including infection, incapacitation, and treatment—along with a time stamp and current location. EpiSims can also produce a representation of the social network, i.e. the person-to-person contact patterns within the entire population and a description of the outbreak path over the social network. It allows for efficient measuring of the structural properties of very large social networks.
If Smallpox Strikes Portland...
Scientific American, March 2005.
"Episims" unleashes virtual plagues in real cities to see how social networks spread disease. That knowledge might help stop epidemics.
By Chris L. Barrett, Stephen G. Eubank, and James P. Smith
S. Eubank, V.S. Anil Kumar, M. Marathe, A. Srinivasan, and N. Wang. Structure of Social Contact Networks and Their Impact on Epidemics. To appear in AMS-DIMACS Special Volume on Epidemiology.
C. Barrett, S. Eubank, and M. Marathe. Modeling and Simulation of Large Biological, Information, and Socio-Technical Systems: An Interaction-Based Approach. To appear in Interactive Computing: A New Paradigm, Ed. D. Goldin, S. Smolka, and P. Wegner Springer Verlag, 2005.
C. Barrett, S. Eubank, V.S. Anil Kumar, and M. Marathe. Understanding Large-Scale Social and Infrastructure Networks; A Simulation-Based Approach. SIAM News 4, May 2004.
S. Eubank. Mathematics of Epidemiological Simulations for Response
Planning. The Mathematical Sciences' Role in Homeland Security,
Board on Mathematical Sciences and Their Applications,
National Academies Press, 2004: 166–187.
C. Barrett, S. Eubank, M. Marathe, H. Mortveit, A. Srinivasan, and N. Wang. Structural and Algorithmic Aspects of Massive Social Networks. Proc. 15th annual ACM-SIAM Symposium on Discrete Algorithms, New Orleans, 2004: 718–727.