Efficient detection of SARS-CoV-2 IgG by a smartphone-based high-throughput fiber optic sensor
The World Health Organization has indicated that Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2) is likely to persist for an extended period, with the potential emergence of new mutated strains. To effectively control the spread of the virus, there is an urgent need for simple, rapid, and reliable assays to identify SARS-CoV-2 infections, particularly in community hospitals or clinical centers. This study introduces a smartphone-based high-throughput fiber-optic immunosensor (HFIS) for rapid SARS-CoV-2 IgG detection. The system significantly improves upon existing methods by combining laboratory-level accuracy with point-of-care convenience. Key advantages include: (1) 100-fold higher throughput than typical smartphone lateral flow readers (100 vs 1 sample/run); (2) 3 × faster than smartphone-ELISA hybrids (40 vs 120+ minutes); (3) Enhanced sensitivity with 86.05 % detection rate versus 83.72 % for commercial ELISA; (4) Lower cost than multi-well smartphone readers by eliminating movable parts; (5) True portability as a 259g standalone device versus bulkier smartphone attachments; and (6) Laboratory-level accuracy (AUC = 0.96) surpassing most smartphone-based assays (typically AUC<0.90).This integrated solution addresses critical needs for large-scale screening, offering rapid, high-throughput testing with laboratory-quality results in field settings. The technology's modular design also allows potential adaptation for other infectious disease diagnostics.
Authors
- Ning Deng (ORCID: https://orcid.org/0000-0002-0467-0146)
- Anni Ding (ORCID: https://orcid.org/0000-0003-0081-6678)
- Shangwu Wang
- Wei Xiao (ORCID: https://orcid.org/0000-0001-8809-9137)
- Si Wang (ORCID: https://orcid.org/0000-0003-4958-3668)
- Hongjie Wei
- Hong Wang (ORCID: https://orcid.org/0009-0008-9183-8306)
Institutions
- Jinan University (CN)
- Second Affiliated Hospital of Guangzhou Medical University (CN)
- Qujiang People's Hospital (CN)
- Guangzhou Medical University (CN)
Publication Details
- Journal
- Talanta
- Published
- 2025-04-24
- DOI
- https://doi.org/10.1016/j.talanta.2025.128183
- Citations
- 1
- Primary Topic
- SARS-CoV-2 detection and testing
- Type
- article
- Field-Weighted Citation Impact
- 1.40