Nonlinear expansion, spatial diffusion, and climate-driven dynamics of scorpionism in Brazil: a nationwide time-series and DLNM analysis (2007-2025).

Scorpionism has emerged as a growing public health concern in Brazil, characterized by increasing incidence and geographic expansion. Despite this trend, studies integrating climatic drivers and advanced time-series modeling remain limited. This study aims to analyze the temporal dynamics, spatial diffusion, and climate-disease relationships of scorpion sting incidence in Brazil using a nationwide dataset from 2007 to 2025. Monthly scorpion sting data from SINAN/DATASUS were combined with high-resolution climatic variables from the TerraClimate dataset. Descriptive statistics, seasonal analysis, and lagged correlation were applied to explore temporal patterns. A distributed lag non-linear model (DLNM) was used to quantify the non-linear and delayed effects of temperature and precipitation on scorpion sting incidence. The results revealed a pronounced non-linear increase in scorpionism, with a structural breakpoint around 2011 indicating accelerated expansion. Seasonal patterns showed higher incidence between September and November. Lag analysis demonstrated that temperature had the strongest association with incidence, peaking at a one-month lag (r ≈ 0.57), while precipitation exhibited weaker but delayed effects. DLNM results confirmed significant non-linear and lag-dependent relationships, with elevated temperatures associated with increased risk at short lag periods. Scorpionism in Brazil is a climate-sensitive and dynamically evolving epidemiological system, driven by the interaction of environmental variability and urban expansion. These findings highlight the need for integrated, climate-informed public health strategies and predictive modeling approaches to mitigate future risk.