Forecasting tuberculosis incidence in Brazil: Time series analysis of trends and impacts of the COVID-19 Pandemic
INTRODUCTION: Tuberculosis remains a persistent public health challenge in Brazil, with a significant increase in cases since 2015, hindering progress toward the disease control targets established by the Sustainable Development Goals. OBJECTIVE: This study aimed to analyze trends in tuberculosis incidence in Brazil, using time series models to predict the disease trajectory through 2030. The Holt-Winters and SARIMA models were used to adjust historical data and make future predictions, taking into account the impact of the COVID-19 pandemic on disease detection between 2020 and 2021. METHODOLOGY: The methodology included time series analysis, model comparison, and an assessment of the limitations associated with data from the Disease Notification System and socioeconomic factors. RESULTS: The results indicated that tuberculosis incidence began toincrease significantly from 2015, with a temporary decline during the pandemic, followed by a new increase until 2022. Predictions through 2030 suggest that if the trend continues, incidence may return to the alarming levels observed in the early 2000s. The analysis also revealed limitations in the data, such as the lack of updated population projections and the exclusion of external factors, such as socioeconomic conditions. CONCLUSION: The study highlights the urgent need for multifaceted interventions, including strengthening the Unified Health System and implementing effective public policies to reverse the increase in tuberculosis and achieve global disease eradication goals. Keywords: COVID-19; Incidence; Tuberculosis; Time Factors