Local survival of spread of infection among biased random walks

Abstract

We study infection spread among biased random walks on Z d . The random walks move independently and an infected particle is placed at the origin at time zero. Infection spreads instantaneously when particles share the same site and there is no recovery. If the initial density of particles is small enough, the infected cloud travels in the direction of the bias of the random walks, implying that the infection does not survive locally. When the density is large, the infection spreads to the whole Z d . The proofs rely on two different techniques. For the small density case, we use a description of the infected cloud through genealogical paths, while the large density case relies on a renormalization scheme.

Local and global survival for infections with recovery

“…[7] provides lower and upper bounds for the speed of infection spread, while [9] strengthens these bounds to a full shape theorem. Following the same line, Baldasso and Stauffer [1] consider infection processes spreading on top of biased random walks, and prove the existence of a phase transition for local survival of the infection.…”