Evidence mapPaperPMID 42584103Full record

ReviewChemical reviews2026

Surface-Enhanced Raman Spectroscopy for Viral Diagnostics: Principles, Strategies, Clinical Challenges, and Future Directions.

Yanjun Yang, Yiping Zhao

Abstract readReview
PubMed Publisher
In one paragraph

Review in Chemical reviews, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yanjun YangDepartment of Physics and Astronomy, The University of Georgia, Athens, Georgia30602, United States.ORCID 0000-0002-1822-7364
Yiping ZhaoDepartment of Physics and Astronomy, The University of Georgia, Athens, Georgia30602, United States.ORCID 0000-0002-3710-4159

Funding

National Institute of Food and Agriculture 2023-67015-39237U.S. Department of Agriculture AP230A000000C009
6 · The paper itself

Abstract

Viral outbreaks such as SARS-CoV, MERS-CoV, and COVID-19 underscore the urgent need for rapid, sensitive, and scalable diagnostic technologies. Current standard methods, including nucleic acid amplification tests and immunoassays, offer complementary strengths but face limitations in cost, turnaround time, and early-stage detection. Surface-enhanced Raman spectroscopy (SERS) has emerged as a promising alternative, leveraging plasmonic nanostructures to amplify weak Raman signals and provide molecular "fingerprints" of viral components with single-molecule sensitivity. This review provides a comprehensive overview of SERS-based virus detection, highlighting the fundamental principles of Raman enhancement, the role of substrates and hotspots, and analyte-specific challenges. We categorize sensing strategies into direct detection of intact viruses and components, affinity-based approaches using antibodies, aptamers, or viral receptors, and labeled methods that amplify specificity and multiplexing. Advances in nanofabrication, receptor engineering, and machine learning have significantly improved sensitivity, reproducibility, and classification accuracy, with detection limits reaching down to a few viral particles per milliliter. Despite these advances, challenges remain in handling biological complexity, ensuring reproducibility, and translating assays into clinical practice. We conclude by outlining opportunities for integrating SERS with portable devices, standardized spectral libraries, and artificial intelligence, paving the way toward rapid, robust, and deployable viral diagnostics for future pandemic preparedness.

Indexed as

COVID-19SARS-CoV-2Spectrum Analysis, RamanVirusesHumansRapid Diagnostic Tests

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.