Our evaluation suggests that ABM models were able to capture the dynamic nature of the epidemic for a longer duration of time while CCMs performed inefficiently. Out of these models in our suite, ABM was able to capture the data better than CCMs. We optimized ABM and CCMs and evaluated them on multiple error metrics.
Our tool allows simulation of scenarios by changing the strength of lockdown, basic reproduction number(R0), asymptomatic spread, testing rate, contact rate, recovery rate, incubation period, leakage in lockdown etc. These had been deployed to create an interactive dashboard called COVision which includes the Agent-based Models (ABM) and classical compartmental models (CCM). In this paper, we developed a suite of models to guide the development of policies under different scenarios when the lockdown opens. Although many models have been developed all around the world, transparent models that allow interacting with the assumptions will become more important as we test various strategies for lockdown, testing and social interventions and enable effective policy decisions. 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 adjustment.ĬOVID-19 pandemic is an enigma with uncertainty caused by multiple biological and health systems factors. The right figure does show all necessary adjustments to expand the SIR-to a SIRS-type epidemic (additional state transition highlighted). Especially modifications and/or extensions of the final model can be handled in an elegant way. Using AnyLogic as implementation platform agents and especially state charts can be programmed very conveniently. Setting up a SIR-type model using the AB approach one can take advantage of state charts to control the behavior of agents. CA and MAS are so called "bottom-up" 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. The difference between the approach with differential equations and the latter two methods is big. 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). Ordinary differential equations (ODE) and Partial differential equations (PDE) have dominated this field for several decades, if not centuries. The number of different methods used on this problem is not too small either.
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The question how to model the spread of epidemics has been approached countless times.
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