A distributed dynamics for virus-spread control

Inspired by a local version of the replicator dynamics, this work proposes a discrete-time distributed algorithm that allows a connected group of nodes to dynamically achieve virus spreading minimization subject to operational constraints. The proposed algorithm is distributed in the sense that it can be implemented by network nodes via local and anonymous interactions. By employing a discrete-time LaSalle invariance principle, we obtain a bound on the algorithm step size that guarantees asymptotic convergence under time-varying interactions. The performance of the method is illustrated on simulation examples.