Implementação e integração de uma arquitetura de software para simulações de propagação de doenças em animais

Abstract

Disease propagation prediction systems have gained prominence, especially following the COVID-19 pandemic. They are valuable tools for controlling the spread of infectious diseases and optimizing resource allocation for research and development. The MHASpread model is an intelligent system that uses real data to simulate the spread of diseases in animals such as cattle, swine, and small ruminants. This system allows researchers to test different control strategies for these diseases, providing valuable information for public health interventions. However, the current version of the system is accessible only to users with programming knowledge and requires substantial computational resources, representing a significant barrier to adoption by veterinary professionals. This work aims to improve the scalability and accessibility of the model, allowing epidemiologists and animal health professionals to efficiently input data, run simulations, and visualize results intuitively. The new software architecture will support parallel user requests and aggregate information into charts and maps. Integrated with the Animal Health Defense Platform (PDSA-RS), the proposed architecture will eliminate the need for users to configure their environment, offering an effective tool to simulate disease spread and assess the impact of implemented control measures. The proposed architecture was evaluated and tested during a disease spread training session held at the State Secretariat of Agriculture, Livestock, Sustainable Production and Irrigation (SEAPI), with the participation of about twenty state veterinarians. At the end of the training, it was concluded that the work achieved its goal of supporting multiple users executing in parallel, as well as contributing as a tool to assist in the decision-making of the involved users.