  In this paper we consider the epidemic competition between two generic
diffusion processes, where each competing side is represented by a different
state of a stochastic process. For this setting, we present the Generalized
Largest Reduction in Infectious Edges (gLRIE) dynamic resource allocation
strategy to advantage the preferred state against the other. Motivated by
social epidemics, we apply this method to a generic continuous-time SIS-like
diffusion model where we allow for: i) arbitrary node transition rate functions
that describe the dynamics of propagation depending on the network state, and
ii) competition between the healthy (positive) and infected (negative) states,
which are both diffusive at the same time, yet mutually exclusive on each node.
Finally we use simulations to compare empirically the proposed gLRIE against
competitive approaches from literature.
