Related Experiment Video
Updated: Jul 9, 2026

Microfluidic Chip Fabrication and Method to Detect Influenza
Published on: March 26, 2013
Next-Generation Diagnostic Technologies for Dengue Virus Detection: Microfluidics, Biosensing, CRISPR, and AI
Salim El Kabbani1, Gameel Saleh1
1Department of Biomedical Engineering, College of Engineering, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.
None:
Dengue fever remains a major mosquito-borne disease worldwide, with over 400 million infections annually and a high risk of severe complications such as dengue hemorrhagic fever. The disease is prevalent in tropical and subtropical regions, where population density and limited vector control accelerate transmission, making early and reliable diagnosis essential for outbreak prevention and disease management. Conventional diagnostic methods, including virus isolation, reverse transcription polymerase chain reaction (RT-PCR), enzyme-linked immunosorbent assays (ELISA), and serological testing, are accurate but often constrained by high cost, labor-intensive procedures, centralized laboratory requirements, and delayed turnaround times. This review examines current dengue diagnostic technologies by outlining their working principles, performance characteristics, and practical limitations, with emphasis on key target analytes such as viral RNA; nonstructural protein 1 (NS1), including DENV-2 NS1; and host antibodies. Diagnostic approaches across commonly used biofluids, including whole blood, serum, plasma, and urine, are discussed. Recent advances in biosensing technologies are reviewed, including optical, electrochemical, microwave, microfluidic, and CRISPR-based platforms, along with the integration of artificial intelligence for data analysis and diagnostic enhancement. Overall, this review highlights the need for accurate, scalable, and field-deployable diagnostic solutions to support early dengue detection and reduce the global disease burden.
Related Concept Videos
Methods of Classification and Identification
Modern Molecular Taxonomy
Methods to Assess Microbial Populations
Microbial Biosensors
Rapid Identification of Pathogens
Automated Microbial Diagnostics

