  To describe the dynamics of social distancing during pandemics, we follow
previous efforts to combine basic epidemiology models (e.g. SIR - Susceptible,
Infected, and Recovered) with game and economy theory tools. We present an
extension of the SIR model that predicts a series of discontinuous transitions
in social distancing. Each transition resembles a phase transition of the
second-order (Ginzburg-Landau instability) and, therefore, potentially a
general phenomenon. The first wave of COVID-19 led to social distancing around
the globe: severe lockdowns to stop the pandemic were followed by a series of
lockdown lifts. Data analysis of the first wave in Austria, Israel, and Germany
corroborates the soundness of the model. Furthermore, this work presents
analytical tools to analyze pandemic waves, which may be extended to calculate
derivatives of giant components in network percolation transitions and may also
be of interest in the context of crisis formation theories.
