FULLY AGENT BASED MODELLINGS OF EPIDEMIC SPREAD USING ANYLOGIC

Abstract

The question how to model the spread of epidemics has been approached countless times. The number of different methods used on this problem is not too small either. Ordinary differential equations (ODE) and Partial differential equations (PDE) have dominated this field for several decades, if not centuries. In the second half of the last century two alternative techniques appeared on the stage, namely cellular automata (CA) and agent based (AB) models, also called multi agent systems (MAS). The difference between the approach with differential equations and the latter two methods is big. CA and MAS are so called “bottomup” approaches, focusing on the smallest unit of the system – a cell or agent, whereas ODEs try to model the system via causal connections on the macroscopic level. Setting up a SIR-type model using the AB approach one can take advantage of state charts to control the behavior of agents. Using AnyLogic as implementation platform agents and especially state charts can be programmed very conveniently. Especially modifications and/or extensions of the final model can be handled in an elegant way. The right figure does show all necessary adjustments to expand the SIR- to a SIRS-type epidemic (additional state transition highlighted). The results obtained by simulation with such an MAS are comparable to those of the ODE- and CA-approach, although AB modeling offers a higher degree of freedom and thus more possibilities of