Name
Title | ||
|---|---|---|
A hybrid epidemic model: combining the advantages of agent-based and equation-based approaches |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/WSC.2007.4419767 | Winter Simulation Conference |
Keywords | Field | DocType |
epidemic process,human behavior,equation-based approach,hybrid model,detailed population structure,computational time,disciplined approach,agent-based model,equation-based model,joint behavior,hybrid epidemic model,population-averaged approach,mathematical analysis,epidemic model | Epidemic model,Agent-based model,Computer science,Simulation,Artificial intelligence,Spurious relationship,Population structure | Conference |
ISBN | Citations | PageRank |
1-4244-1306-0 | 24 | 1.95 |
References | Authors | |
1 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Georgiy V. Bobashev | 1 | 31 | 4.05 |
| D. Michael Goedecke | 2 | 25 | 2.33 |
| Feng Yu | 3 | 24 | 1.95 |
| Joshua M. Epstein | 4 | 297 | 45.07 |