Agent-based Modeling as a Tool for Predicting the Spatial-temporal Diffusion of the COVID-19 Pandemic

ABSTRACT

The article presents the original methodology of using agent-based modeling (ABM) for the numerical simulations of the COVID-19 pandemic's development. The proposed solution makes it possible to analyze changes in the number of cases both in space and time. The devised methodology enables considering spatial conditions in terms of population distribution, such as places of work, rest, or residence, and uses multi-agent modeling to consider spatial interactions. Numerical simulations utilize the spatial and demographic data in GIS databases and the GAMA environment that enables the parameterization of the epidemiological model. Testing the developed methodology on a test area also allowed for checking the effects of a potential decrease or increase in social restrictions numerically. The simulations performed show a high correlation between the level of social distancing and the number of COVID-19 cases. © 2021 IEEE.