Our team has a wealth of experience in multiagent-based modeling and social simulation. These methods are particularly suited for simulating the spread of infectious diseases. Based on our existing model for the spread of Influenza (Timm und Lasner, 2013) we recently developed a new simulation model for analyzing COVID-19. We use NetLogo as a simulation platform in this case because it is the interdisciplinary de-facto standard for agent-based social simulation.
The new COVID-19 simulation model allows for comparing the spread and impacts of that disease with the common flu (Influenza). Moreover, private and political measures for containing the disease by social distancing can be put in place in this model. In our simulations, we evaluate the effectiveness of these measures.
In its core, our model consists of artificial agents that represent people, households, schools, hospitals, workplaces, and leisure facilities. Links between these agents form possible contacts by which the simulated disease can spread. We researched the modeled mechanisms and derived parameter values from available scientific papers and data sources. Among other sources, we used data and publications from the Imperial College in London, the European Centre for Disease Prevention and Control (ECDC) und the German Robert-Koch-Institute.
