Projects per year

## 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.

Original language | English |
---|---|

Article number | 135 |

Pages (from-to) | 1-28 |

Journal | Electronic Journal of Probability |

Volume | 27 |

Early online date | 6 Oct 2022 |

DOIs | |

Publication status | E-pub ahead of print - 6 Oct 2022 |

## Keywords

- biased random walks
- infection processes
- interacting particle systems

## ASJC Scopus subject areas

- Statistics and Probability
- Statistics, Probability and Uncertainty

## Fingerprint

Dive into the research topics of 'Local survival of spread of infection among biased random walks'. Together they form a unique fingerprint.## Projects

- 1 Finished