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.

这项工作揭示了一种流行病学数学模型，以预测对铜绿假单胞菌感染的狗的治疗方法。这种危险的病原体是引起多重耐药性感染的主要原因之一，并且可以从狗传播给人类。使用Matlab开发了数值模拟和适当的代码该软件可收集有关易感，感染和康复者的长期动态的信息。从数学模型收集的所有数据均用于为这种特定感染提供适当的抗生素敏感性面板。在这项研究中，该模型中包含了几个变量，以预测在没有时间进行抗菌素检查或无法承担其成本的情况下应在紧急情况下应采取的治疗方法。特别是，我们着重指出了该模型的使用，旨在成为设计细菌病原体缓解策略时公共卫生研究和决策的便捷工具箱的一部分。