Simulações de cenários epidemiológicos utilizando modelos baseados em agentes

Abstract

In the field of supplementary health, the decision-making process needs to be increasingly innovative to adapt to the new realities. The epidemiological study process can provide valuable information to support the decision-making process in the health area. The present work aims to develop a simulator to assist in decision-making in the epidemiological and care area, exploring the computational capacity to generate several simulations, based on the Monte Carlo Theorem. For this, an algorithm was developed that, combining the Agent-Based Model technique applied to the SEIR model methodology, simulates several epidemiological scenarios in order to analyze the behavior of a fictitious population. In addition to creating the simulator algorithm, an application was also developed to assist in the analysis of simulated epidemiological scenarios and facilitate its interaction with the user, using the R programming language in its construction. In this way, a tool was developed to help professionals in the area to create simulations in order to supplement their decision-making processes and expense estimates.