  This work discloses an epidemiological mathematical model to predict an
empirical treatment for dogs infected by Pseudomonas aeruginosa. This dangerous
pathogen is one of the leading causes of multi-resistant infections and can be
transmitted from dogs to humans. Numerical simulations and appropriated codes
were developed using Matlab software to gather information concerning long-time
dynamics of the susceptible, infected and recovered individuals. All data
compiled from the mathematical model was used to provide an appropriated
antibiotic sensitivity panel for this specific infection. In this study,
several variables have been included in this model to predict which treatment
should be prescribed in emergency cases, when there is no time to perform an
antibiogram or the cost of it could not be assumed. In particular, we highlight
the use of this model aiming to become part of the convenient toolbox of Public
Health research and decision-making in the design of the mitigation strategy of
bacterial pathogens.
