  Coffee rust is one of the main diseases that affect coffee plantations
worldwide. This causes an important economic impact in the coffee production
industry in countries where coffee is an important part of the economy. A
common method for combating this disease is using copper hydroxide as a
fungicide, which can have damaging effects both on the coffee tree and on human
health. A novel method for biological control of coffee rust using bacteria has
been proven to be an effective alternative to copper hydroxide fungicides as
anti-fungal compounds. In this paper, we develop and explore a spatial
stochastic model for this interaction in a coffee plantation. We analyze
equilibria for specific control strategies, as well as compute the basic
reproductive number, R0, of individual coffee trees, conditions for local and
global stability under specific conditions, parameter estimation of key
parameters, as well as sensitivity analysis, and numerical experiments under
local and global control strategies for key scenarios.
