Advances in influenza A and B virus detection: molecular diagnostics, biosensors, and point-of-care applications.

Authors

Yingqi Huang, Chen Duan, Xiyan Deng, Xinlan Zhang, Meiqi Wu, Siqin Peng, Rushi Liu, Defu Hou

Published in

Journal of microbiological methods. Pages 107746. Oct 17, 2026. Epub Oct 17, 2026.

Abstract

Influenza A and B viruses remain major causes of seasonal epidemics and continue to pose substantial challenges for rapid clinical diagnosis and public-health surveillance. Conventional methods, including viral culture, immunological assays, and reverse-transcription real-time quantitative PCR (RT-qPCR), provide important diagnostic benchmarks but are constrained by long turnaround times, dependence on specialized equipment, or reduced sensitivity in low-viral-load specimens. This review summarizes recent advances in influenza virus detection, with emphasis on molecular diagnostics, biosensors, point-of-care testing, and high-throughput sequencing. Digital PCR offers precise absolute quantification, whereas isothermal amplification technologies such as reverse transcription loop-mediated isothermal amplification (RT-LAMP) and reverse transcription recombinase polymerase amplification (RT-RPA) reduce reliance on thermal cycling and support portable testing. CRISPR-Cas systems further improve sequence specificity and are increasingly being integrated with isothermal amplification, lateral-flow readouts, and microfluidic platforms. Biosensor strategies based on optical, electrochemical, multimodal, and smartphone-assisted readouts provide promising routes for rapid, multiplexed, and point-of-care detection, although standardization and large-scale clinical validation remain key barriers. High-throughput sequencing complements rapid testing by enabling viral typing, variant monitoring, and emerging-pathogen monitoring. Overall, future influenza diagnostics are expected to move toward integrated, low-cost, "sample-in, answer-out" systems that combine sensitivity, speed, portability, and surveillance connectivity.

PMID:
42892439
Bibliographic data and abstract were imported from PubMed on 18 Oct 2026.

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