Title: Game-Theoretic Choice of Curing Rates Against Networked SIS Epidemics by Human Decision-Makers,
Abstract: We study networks of human decision-makers who independently decide how to
protect themselves against Susceptible-Infected-Susceptible (SIS) epidemics.
Motivated by studies in behavioral economics showing that humans perceive
probabilities in a nonlinear fashion, we examine the impacts of such
misperceptions on the equilibrium protection strategies. In our setting, nodes
choose their curing rates to minimize the infection probability under the
degree-based mean-field approximation of the SIS epidemic plus the cost of
their selected curing rate. We establish the existence of a degree based
equilibrium under both true and nonlinear perceptions of infection
probabilities (under suitable assumptions). When the per-unit cost of curing
rate is sufficiently high, we show that true expectation minimizers choose the
curing rate to be zero at the equilibrium, while curing rate is nonzero under
nonlinear probability weighting.