Determinants and Spatial Patterns of Dengue Severity in Brazil: A Nationwide Cross-sectional Analysis of Surveillance Data

Abstract

Background: Dengue remains a major public health challenge in endemic countries, with increasing incidence and severity. Understanding the determinants of severe disease at a national level is essential to guide surveillance and control strategies. Methods: We conducted a nationwide cross-sectional study using surveillance data from the Brazilian Notifiable Diseases Information System (SINAN) for 2025. A total of 825,586 confirmed dengue cases with valid outcome data were included. Multinomial logistic regression was used to identify factors associated with disease severity. Spatial analysis was performed using incidence rates per 100,000 inhabitants across states. Findings: Most cases were classified as dengue without warning signs (97.3%), followed by dengue with warning signs (2.5%) and severe dengue (0.2%). Increasing age was associated with higher odds of severe dengue (OR=1.01 per year; 95% CI 1.006–1.014). The presence of comorbidities showed a strong association, with a clear dose–response pattern according to the morbidity index. Individuals without comorbidities had a 69% lower likelihood of severe dengue compared to those with multiple conditions. RT-PCR-confirmed cases were more likely to be severe (OR=1.93; 95% CI 1.51–2.46). Spatial analysis revealed marked heterogeneity, with the highest incidence observed in Goiás (1,280.79 cases per 100,000 inhabitants) and similar patterns for severe dengue. Interpretation: Dengue severity in Brazil is driven by a combination of demographic, clinical, and contextual factors. Targeted surveillance and clinical management strategies focusing on high-risk groups and high-incidence regions may reduce disease burden and mortality.