Fluid Model-Checking in UPPAAL for Covid-19

During the spring of 2020, the BEOCOVID project has been funded to investigate the use of stochastic hybrid models, statistical model checking and machine learning to analyse, predict and control the rapid spreading of Covid-19. In this paper we focus on the SEIHR epidemiological model instance of Covid-19 pandemics and show how the risk of viral exposure, the impact of super-spreader events as well as other scenarios can be modelled, estimated and controlled using the tool. © 2020, Springer Nature Switzerland AG.