Agent-Based Modelling of the spread of COVID-19 in Corsica

ABSTRACT

The modelling epidemiology processes supporting public policy decision-making usually require SIR compartmental models which mathematically describe the pandemic phenomenon's dynamics. In general, these models and extensions are used to conceptualize a macro-level of populations evolving between different pre-determined health statuses. In this work, we propose an alternative modelling for the COVID-19 pandemic according to probabilities defined by interactions among individuals. We present an Agent-Based Model (ABM) to take into account both the heterogeneity of individuals population health statuses and the spatial structure of the environment. The model is verified by reproducing already known results of Corsica's COVID-19 pandemic data and different patterns of COVID-19 virus spread are visualized at any time with the NetLogo simulation environment. The implementation details of our alternative approach is then detailed and discussed.