  The spread of traffic jams in urban networks has long been viewed as a
complex spatio-temporal phenomenon that often requires computationally
intensive microscopic models for analysis purposes. In this study, we present a
framework to describe the dynamics of congestion propagation and dissipation of
traffic in cities using a simple contagion process, inspired by those used to
model infectious disease spread in a population. We introduce two novel
macroscopic characteristics of network traffic, namely congestion propagation
rate \b{eta} and congestion dissipation rate {\mu}. We describe the dynamics of
congestion propagation and dissipation using these new parameters, \b{eta}, and
{\mu}, embedded within a system of ordinary differential equations, analogous
to the well-known Susceptible-Infected-Recovered (SIR) model. The proposed
contagion-based dynamics are verified through an empirical multi-city analysis,
and can be used to monitor, predict and control the fraction of congested links
in the network over time.
