Abstract

When humanity faces a potentially contagious disease, most processes of society are affected, the workforce capable of performing tasks decreases, and healthcare systems become overwhelmed by sudden disease outbreaks. In 2020, the world fell victim to Covid-19. Its spread had devastating consequences in many countries, changing the lives of all individuals. The poor management of the pandemic on a global scale highlighted the lack of preparedness for this type of catastrophe, leading to efforts and research being conducted to facilitate the management of this disease. One of the most important endeavors undertaken to control the spread of the infectious virus was to attempt to predict its behavior and take measures to mitigate the damage caused. Pandemic control models, such as the SEIR model, were employed to create predictions, but the results proved to be imprecise due to the lack of infection data. Furthermore, a highly contagious virus that is transmitted by people behaves in a very erratic manner, making it more challenging to develop rigid prediction methods. It was determined that geographic and demographic characteristics greatly influenced the virus's behavior. Agent-Based Simulation was used to model processes and environments with unique characteristics while allowing for individual interaction. In this work, Agent-Based Simulation is employed to model the spread of a virus that affects individuals in a city in Cuba.