Climate Variability and Dengue Dynamics: A Path Analysis in Surabaya, Indonesia
TL;DR
It is demonstrated that dengue dynamics in tropical metropolitan environments are governed by complex climate-mediated pathways rather than isolated climatic predictors under climate variability and urban environmental change.
Abstract
Introduction: Dengue fever is a climate-sensitive vector-borne disease. While many studies have documented associations between climate variables and dengue incidence, most rely on conventional regression approaches that fail to separate direct and indirect climatic pathways, limiting mechanistic understanding and utility for environmental health. This study aims to elucidate the interconnected effects of climatic variability on dengue incidence in Surabaya. This study integrates seasonal time-series decomposition and path analysis to distinguish direct and indirect climatic pathways, sunlight duration and wind speed. Methods: A retrospective ecological design, monthly dengue incidence data from 2020 to 2024 were integrated with meteorological variables, including rainfall, temperature, humidity, sunlight duration, and wind speed. Seasonal time-series decomposition was applied to characterize temporal dynamics, followed by path analysis within a structural equation modeling framework to quantify direct and indirect climatic effects. Results and Discussion: A pronounced seasonal pattern in dengue incidence, with peaks during the rainy season. Maximum temperature, relative humidity, sunlight duration, and minimum wind speed exerted significant direct effects on dengue incidence (p < 0.05). Rainfall showed no direct association but acted as a key upstream driver influencing other climatic variables. The structural model explained 52.1% of the variance in dengue incidence, highlighting the contribution of interconnected climatic processes. Conclusion: These findings demonstrate that dengue dynamics in tropical metropolitan environments are governed by complex climate-mediated pathways rather than isolated climatic predictors. This study novel environmental epidemiological evidence to support climate-informed dengue early warning systems and adaptive vector control strategies under climate variability and urban environmental change.