A Discrete-event modeling method to study human behavior for spread of diseases on university campuses

• Architecture to study diffusion processes in multiplex networks applied to diseases. • Discrete Event System Specification used for parameterized model. • CO2 concentration in enclosed spaces used as proxy for airborne diseases. • Modeling spread of disease in workplaces accounting for human behavior. • University campus case study tests disease spread mitigation policy. The COVID-19 pandemic has highlighted the importance of defining sound policies to make attending workplaces safer. Sometimes, deciding on different policies is challenging as this highly depends on the behavior of the individuals. This research introduces a Discrete Event-based methodology and a prototype implementation to study such policies, including human behavior along with information about the workplace layout and building characteristics such as ventilation rate or room capacity. The method is based on a combination of agent-based models, diffusion processes and discrete-event simulation. We exemplify how to use this method using a case study based on Carleton University’s Campus, in which we use the methodology and tools to study the effect of ventilation, as well as the application of a policy where sick students are denied entry to the campus on the number of disease cases on campus.