Recent Advances in Surface-Enhanced Raman Spectroscopy for Virus Detection

Since the onset of the COVID-19 pandemic in 2020, the importance of virus detection and development of new diagnostics for emerging or evolving viruses has been a major focus in the field of bioanalytical sensing. Surface-enhanced Raman spectroscopy (SERS) is one technique for virus detection that has taken off in academic research but has not yet transitioned into widespread commercial use despite its enormous potential as a sensitive and specific sensing technology. Herein, we briefly summarize advances in SERS as applied to virus detection over the past 5 years, as there has been rapid development and growth resulting from the need to develop COVID-19 sensors, including critical analysis of the directions of the field. We compare label-free and labeled detection schemes and highlight machine-learning-enabled sensing, with a focus on viruses relevant to human health. Opportunities are proposed and understudied areas are identified in virus SERS sensing alongside outlooks for the field, including the use of moderate affinity agents to facilitate multiplex sensing and adaptation of machine learning algorithms from fields beyond sensing.