Significance Viruses are the primary cause of many infectious diseases, including influenza, highmortality 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 lifethreatening 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 largescale testing in rapidly spreading virusinfected areas.Surfaceenhanced Raman scattering (SERS) technology is an ultrasensitive vibrational spectroscopy technique, which is used to detect plasmonic on the surface or nearsurface molecules. Due to its fast response, strong specificity, and noninvasive 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 特邀综述 第 51 卷 第 9 期/2024 年 5 月/中国激光 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 onsite and realtime 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.