Surface-enhanced Raman scattering (SERS) technology is an ultra-sensitive vibrational spectroscopy technique, which is used to detect plasmonic nanostructures on the surface or near-surface molecules. Due to its fast response, strong specificity, and non-invasive detection characteristics, SERS has been widely used in surface and interface studies, chemical and biosensors, biomedical monitoring, trace analysis, electrochemical reactions, and catalytic reactions. Specifically, in virus detection, it exhibits extremely high detection sensitivity, enabling rapid and accurate detection of minute virus particles. Based on the analysis of virus spectral features, SERS technology can differentiate between different types of viruses, including subtypes and variants. This high specificity leads to a unique advantage in virus tracing, classification, and epidemiological research, which is crucial for the rapid screening of early virus infections and facilitating timely medical intervention. This review systematically summarizes the research progress and potential applications of SERS technology in virus detection over the past two years, considering factors such as the genetic material of the virus, virus types, and the extent of impact (Fig.1).

Progress Initially, this study categorizes viruses based on their genetic material, focusing on recent efforts to detect RNA and DNA viruses that threaten human life and health. It offers a comprehensive analysis of both labeled and label-free SERS techniques for detecting these virus types. For RNA viruses, such as SARS-CoV-2, the influenza virus, HIV, and DNA viruses, such as HBV and HPV, label-free detection methods require SERS technology to realize enhanced performance in signal amplification of the detection substrate for direct detection of natural biomolecules without amplification. Notable examples include the trap structure introduced by Yang et al., the nano-flexible substrate by Paria et al., and the semiconductor application by Peng et al., which broaden the application scope of SERS technology. In the realm of SERS signal processing, particularly when combined with machine learning techniques, there is a significant advantage in extracting and analyzing spectral features for identifying potential biomarkers or molecular details in complex and varied samples. The creation of sensitive SERS biological probes in labeling methods is especially critical. Accurately tagging target molecules with Raman signal molecules greatly increases the specificity of the detection platform. For example, Guan et al. employed substrate capture and specific recognition probes for detecting the SARS-CoV-2 antigen, while Su et al. developed SERS labels integrated with CRISPR/Cas technology for the non-amplified detection of target genes. Moreover, the miniaturization and portability of Raman instruments, propelled by technological advancements, are steering SERS toward field applications and real-time analysis, aligning perfectly with the point-of-care testing (POCT) concept. This foundation supports the study’s summary of various initiatives that combine SERS technology with portable Raman instruments. It concludes by offering a summary and outlook on optimization strategies and the current challenges facing the application of SERS technology in virus detection and various POCT settings.

Conclusions and Prospects The efficacy of SERS technology in virus detection hinges on several critical factors, such as the design of the enhancement substrate, excitation conditions, the properties of labels and analytes, detection devices, and data analysis techniques. The primary aim is to enhance detection speed and sensitivity while simplifying the detection process for more efficient virus identification. To navigate the intricate challenges posed by viral outbreaks, the development of integrated micro-detection chips capable of identifying multiple viruses, paired with compact Raman detection devices, stands as the ideal approach for future POCT of viruses. Furthermore, investigating the integration of SERS technology with other detection methods—such as chemical separation, biological capture, colorimetry, and advanced computational approaches like machine learning, deep learning, and artificial intelligence—can maximize the benefits of diverse technologies. This integration promises the creation of innovative Raman analysis devices that consolidate sample processing, detection, analytical processing, statistical analysis, result dissemination, and display functionalities, catering to the on-site and real-time testing demands across various sectors. We expect that merging SERS technology with compact Raman instruments will usher in a convenient, efficient, and precise optical POCT method for virus screening, classification, infection tracking, and prognosis forecasting.

Viruses are the primary cause of many infectious diseases, including influenza, high-mortality lower respiratory tract infections, diarrhea, tuberculosis, HIV infection, dengue fever, hepatitis B, and more. These diseases can cause severe damage to various systems in the human body and can even lead to life-threatening conditions. The outbreak of infectious viruses poses a significant challenge to public healthcare systems. Early and accurate virus diagnosis is crucial in preventing virus spread, especially in the absence of specific vaccines or effective medications. Existing traditional detection methods often require complex equipment and the expertise of skilled operator. Hence, it becomes challenging to conduct large-scale testing in rapidly spreading virus-infected areas.