PRIMA '08 Proceedings of the 11th Pacific Rim International Conference on Multi-Agents: Intelligent Agents and Multi-Agent Systems
Epidemic marketplace: an information management system for epidemiological data
ITBAM'10 Proceedings of the First international conference on Information technology in bio- and medical informatics
Reversible Parallel Discrete-Event Execution of Large-Scale Epidemic Outbreak Models
PADS '10 Proceedings of the 2010 IEEE Workshop on Principles of Advanced and Distributed Simulation
The impact of the power law exponent on the behavior of a dynamic epidemic type process
Proceedings of the twenty-fourth annual ACM symposium on Parallelism in algorithms and architectures
Recursive simulation and experimental frame for multiscale simulation
SCSC '09 Proceedings of the 2009 Summer Computer Simulation Conference
Proceedings of the Winter Simulation Conference
Computational & Mathematical Organization Theory
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Agent-based models (ABMs) are powerful in describing structured epidemiological processes involving human behavior and local interaction. The joint behavior of the agents can be very complex and tracking the behavior requires a disciplined approach. At the same time, equation-based models (EBMs) can be more tractable and allow for at least partial analytical insight. However, inadequate representation of the detailed population structure can lead to spurious results, especially when the epidemic process is beginning and individual variation is critical. In this paper, we demonstrate an approach that combines the two modeling paradigms and introduces a hybrid model that starts as agent-based and switches to equation-based after the number of infected individuals is large enough to support a population-averaged approach. This hybrid model can dramatically save computational times and, more fundamentally, allows for the mathematical analysis of emerging structures generated by the ABM.