ArticleRevista brasileira de epidemiologia = Brazilian journal of epidemiology2026
Time series analysis (2015-2022): dengue risk scenario in Goiás, Brazil.
Article in Revista brasileira de epidemiologia = Brazilian journal of epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo analyze confirmed cases of dengue in Goiás, Brazil between 2015 and 2022 and to estimate the risk of new outbreaks until 2026.
methodsA time series study using data from the Notifiable Diseases Information System (SINAN) was conducted. Monthly records of cases confirmed by laboratory or clinical-epidemiological criteria were included. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied using the R software (v.4.2.1). Stationarity, trend, seasonality, residual autocorrelation, and model fit were evaluated, with estimates obtained by maximum likelihood and 95% confidence intervals.
resultsDuring the study period, 709,270 confirmed cases were recorded. Epidemics occurred cyclically every two years, with peaks in 2015 (101,261), 2016 (82,077), 2018 (70,794), 2019 (107,589), and 2022 (189,998), interspersed with years of lower incidence such as 2017 and the COVID-19 pandemic years (2020-2021). Serotype replacement was observed preceding major outbreaks. The SARIMA model showed good fit (Akaike Information Criterion - 1768.9; Bayesian Information Criterion - 1786.8) and predicted new peaks in 2025 (177,775 cases) and 2026 (224,100 cases).
conclusionDengue in Goiás displayed recurrent epidemic cycles, pointing to an increase in cases and reinforcing the need for integrated strategies based on prevention and control. The SARIMA model proved useful for surveillance and public health planning, although its accuracy may be influenced by external factors.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.