Algorithm with time series simulation versus auto-adjustment in R for predicting tuberculosis cases in Goiás. v1

It is estimated that, globally, one in four people is infected with Mycobacterium tuberculosis, and approximately 5–10% of these individuals will develop tuberculosis (Tb) over their lifetime. In Goiás, in 2023, 1,499 cases of Tb were reported, representing a 9.42% increase compared to the previous year. This scenario highlights the uncontrolled spread of the disease in Goiás and worldwide, raising significant public health concerns. Predicting Tb cases is an essential tool for controlling the Tb epidemic. We developed an algorithm that constructs a time series model with better parameters than the auto-adjustment model of an R Studio library for prediction. This enabled the estimation of an epidemiological trend for Tb in Goiás. These findings can significantly contribute to the planning of public health actions and decision-making aimed at controlling Tb in the region.