MATSim EpiSim

EpiSim takes the output of a MATSim transport simulation, a record of where every simulated person was and when over a day, and runs an epidemic on top of it.^1,3 Two people who are in the same place at the same time can infect each other.³ The chance depends on how long they were together, the size of the room and how often its air is changed, whether they wore masks, and whether they were indoors or out.^3,4 Infected people then follow a disease course taken from the literature, through symptoms, hospital, intensive care and quarantine.³

The Transport Systems Planning and Transport Telematics group at Technische Universität Berlin built it during the COVID-19 pandemic and announced it in October 2020.^1,3 The main paper, by Sebastian A. Müller, Kai Nagel and six co-authors, appeared in PLOS ONE in October 2021.⁴ It describes a model of Berlin validated against the city's infection curve, in which changes in how often people went out came from mobile phone data.⁴ The model estimated the effect of contact reductions, school closures and holidays, masks, and leisure moving indoors in autumn.⁴ One finding is that cutting contacts has diminishing returns: the first half of the reduction does much more than the second.⁴ The authors write that the results can be used to inform political decisions.⁴

The core code is a Java library under AGPL-3.0, with a separate example project that runs a provided Berlin scenario and shows how to make an input file from any existing MATSim scenario.^1,2 A user needs Java and Maven, and a MATSim run of their own region is the large piece of work.¹ The repository is still being updated as of October 2026.²

What sets EpiSim apart from epidemic models built on contact matrices is that the contacts come from a model of people's daily routes and activities.⁴ Its limit is the same: it is only as good as the transport model underneath.