  Motivated by the ongoing COVID-19 pandemic, this paper investigates
customers' infection risk by evaluating the overlapping time of a virtual
customer with others in queueing systems. Most of the current methodologies
focus on characterizing the risk in stationary systems, which may not apply to
the more practical time-varying systems. As such, we propose an approximation
framework that relies on the fluid limit to compute the expected overlapping
time in time-varying queueing systems. Simulation experiments verify the
accuracy of our approach.
