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Next—Generation Diagnostic Technologies for Dengue Virus Detection: Microfluidics, Biosensing, CRISPR, and AI Approaches

  • Salim El Kabbani
  • , Gameel Saleh*
  • *Corresponding author for this work
  • Imam Abdulrahman Bin Faisal University

Research output: Contribution to journalReview articlepeer-review

Abstract

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.

Original languageEnglish
Article number145
JournalSensors
Volume26
Issue number1
DOIs
StatePublished - Jan 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • artificial intelligence in viral detection
  • biosensor
  • CRISPR diagnostics
  • dengue virus detection
  • electrochemical biosensors (DPV; EIS)
  • microfluidic lab–on–chip
  • NS1 antigen
  • optical biosensors (SPR; LSPR; SERS)

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