Dengue is an acute febrile disease of public health relevance. In Goiás, there has been a marked increase in case incidence over the last ten years, prompting investigation of the disease in children and adolescents. The study aims to analyze the dengue time series (2015–2023) and estimate the risk of infection in children and adolescents. Ecological study based on dengue information from the Notifiable Diseases Information System (SINAN) from 2015 to 2023, in individuals aged 0 to 19 years with dengue confirmed clinically or laboratorially. The Seasonal Autoregressive Integrated Moving Average Model (SARIMA) was used for time-series analysis and for predicting infection risk for the years 2025, 2026, and 2027. To assess the quality of the chosen statistical model, the metrics AIC (Akaike Information Criterion) and BIC (Bayesian Information Criterion) were used. Over the study years, 176,294 dengue cases were reported, showing a seasonal pattern, with cases in 2015 (22,196), 2016 (18,707), 2017 (10,253), 2018 (15,381), 2019 (23,767), 2020 (10,824), 2021 (12,582), 2022 (45,336), and 2023 (17,248). Predominance of cases was observed in the 10–19 age group. Dengue case projections were generated from analysis of the time series from periods prior to vaccine implementation, representing the expected trend in the absence of intervention, in which the estimated average number of dengue cases predicted for the 0–19 age group is: 2025 (34,511), 2026 (20,615), and 2027 (21,783) cases. The SARIMA (0,0,3) 1 (3,0,0) model with the lowest AIC (1687.331) and BIC (1706.171) was the best model, showing stationarity (Dickey-Fuller, p=0.010), seasonality (Kruskal-Wallis, p=0.000), absence of significant trend (Mann-Kendall, p=0.402), and absence of autocorrelation in residuals (Box-Pierce, p=0.917). Application of the SARIMA model showed consistency of the data and the seasonality of dengue in the state of Goiás, indicating growth in the number of cases among children over the years. The results alert to the need for suspicion, identification, and early management of cases, in order to avoid worsening of the disease in this age group, and also provide a reference scenario for comparative analyses with post-vaccination data.
Coelho et al. (Sun,) studied this question.