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Time series analysis (2015-2022): dengue risk scenario in Goiás, Brazil
Ronaldo Rodrigues de Oliveira Junior1, Ana Carolina Figueiredo Modesto1, Leandro do Prado Assunção2
1Universidade Federal de Goiás, School of Pharmacy - Goiânia (GO), Brazil.
Summary
Dengue outbreaks in Goiás, Brazil, show cyclical patterns, with significant peaks predicted in 2025 and 2026. This analysis highlights the need for integrated prevention and control strategies for dengue fever.
Area of Science:
- Epidemiology
- Public Health
- Time Series Analysis
Background:
- Dengue fever poses a significant public health challenge in Goiás, Brazil.
- Understanding historical outbreak patterns is crucial for effective disease control.
Purpose of the Study:
- To analyze confirmed dengue cases in Goiás from 2015 to 2022.
- To forecast the risk of future dengue outbreaks until 2026.
Main Methods:
- Utilized time series analysis of confirmed dengue cases from the Notifiable Diseases Information System (SINAN).
- Applied the Seasonal Autoregressive Integrated Moving Average (SARIMA) model for forecasting.
- Evaluated model fit and estimated future case numbers with 95% confidence intervals.
Main Results:
- Recorded 709,270 confirmed dengue cases between 2015 and 2022.
- Identified cyclical, biennial epidemic patterns with major peaks in 2015, 2019, and 2022.
- The SARIMA model predicted significant dengue peaks in 2025 (177,775 cases) and 2026 (224,100 cases).
Conclusions:
- Dengue in Goiás exhibits recurring epidemic cycles, indicating a rising trend in cases.
- Integrated prevention and control strategies are essential for managing dengue.
- The SARIMA model is a valuable tool for public health surveillance and planning for dengue outbreaks.
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