Biomarker-driven biosensing strategies for early risk stratification in severe dengue.

Dengue is a major global public health burden, with increasing incidence of severe cases associated with high morbidity and mortality. While secondary infection is a major risk factor, severe dengue also occurs in clinically classified primary infection, indicating mechanisms beyond antibody-dependent enhancement. In clinical practice, NS1 antigen and IgM ELISA remain the standard diagnostic tools to confirm dengue exposure. However, these approaches still fall short in achieving the sensitivity, specificity, and prognostic capability required for early identification of patients at risk of severe dengue. Consequently, disease severity is often recognized only after clinical deterioration. Severe dengue is driven by host immune dysregulation, characterized by dynamic changes in cytokines (e.g. IL-10, IL-6 and TNF-α), chemokines, and regulatory microRNAs (e.g., miR-21) that precede critical deterioration. However, their low abundance and temporal variability challenge conventional detection methods. Biosensors integrated with functional materials offer promising platforms for ultrasensitive and decentralized dengue diagnostics, yet most reported sensors remain focused on viral infection confirmation rather than severity prediction. This review presents a biomarker-driven framework that links host-response signatures to biosensor design for multiplexed detection and early risk stratification. We critically evaluate current biosensing platforms such as electrochemical, optical, plasmonic, lateral flow assay (LFA), quartz microbalance crystal (QCM)-based platform, together with biorecognition elements, and material innovations and discuss translational challenges and future directions toward clinically actionable biosensors for severe dengue.