Aplicação de métodos estocásticos em um modelo de resposta do sistema imune humano à vacina da Febre Amarela

Abstract

The Human Immune System (HIS) plays a key role in defending the body against diseases. However, the multi-scale interactions among several of its components make the complete understanding of the mechanisms involved in body defense a very complex task. Mathematical and computational modeling is a tool that can be used for better understanding these mechanisms. This tool aims to mimic the immune system behavior under distinct conditions using, for this purpose, computational simulations. An important area related to the immune system that is not fully understood is its response to vaccination. Despite some individuals develop immunity against disease for which they were vaccinated, in other cases they don’t. This may happen even with the most effective vaccines, such as the Yellow Fever (YF) one: according to clinical studies, it represents a seroconversion rate between 95% to 98%, which means, for every 100 individuals who receive the YF vaccine, about 95 to 98 of them will generate immunological memory, ensuring their protection against the disease. In this work, a simplified computational mathematical model capable of qualitatively simulating the mechanisms related to the generation of immunity due to the YF vaccination is developed. Thereafter, stochastic methods are employed to simulate distinct answers that may happen after vaccination. Some of the answers cannot be obtained with the use of deterministic methods.