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Objective: To conduct a proof-of-concept study of the detection of two synthetic models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using polarimetric imaging. Methods: Two SARS-CoV-2 models were prepared as engineered lentiviruses pseudotyped with the G protein of the vesicular stomatitis virus, and with the characteristic Spike protein of SARS-CoV-2. Samples were preparations in two biofluids (saline solution and artificial saliva), in four concentrations, and deposited as 5-{\mu}L droplets on a supporting plate. The angles of maximal degree of linear polarization (DLP) of light diffusely scattered from dry residues were determined using Mueller polarimetry of 87 samples at 405 nm and 514 nm. A polarimetric camera was used for simultaneous imaging of several samples under 380-420 nm illumination at angles similar to those of maximal DLP. A per-pixel image analysis included quantification and combination of polarization feature descriptors in other 475 samples. Results: The angles (from sample surface) of maximal DLP were 3 degrees for 405 nm and 6 degrees for 514 nm. Similar viral particles that differ only in the characteristic spike protein of the SARS-CoV-2, their corresponding negative controls, fluids, and the sample holder were discerned from polarimetric image analysis at 10-degree and 15-degree configurations. Conclusion: Polarimetric imaging in the visible spectrum has the potential for non-contact, reagent-free detection of viruses in multiple dry fluid residues simultaneously. Further analysis including real SARS-CoV-2 in human samples -- particularly, fresh saliva -- are required. Significance: Polarimetric imaging under visible light could contribute to fast, cost-effective screening of SARS-CoV-2 and other pathogens.

Optical spectroscopic techniques have been commonly used to detect the presence of biofilm-forming pathogens (bacteria and fungi) in the agro-food industry. Recently, near-infrared (NIR) spectroscopy revealed that it is also possible to detect the presence of viruses in animal and vegetal tissues. Here we report a platform based on visible and NIR (VNIR) hyperspectral imaging for non-contact, reagent free detection and quantification of laboratory-engineered viral particles in fluid samples (liquid droplets and dry residue) using both partial least square-discriminant analysis and artificial feed-forward neural networks. The detection was successfully achieved in preparations of phosphate buffered solution and artificial saliva, with an equivalent pixel volume of 4 nL and lowest concentration of 800 TU·μL−1. This method constitutes an innovative approach that could be potentially used at point of care for rapid mass screening of viral infectious diseases and monitoring of the SARS-CoV-2 pandemic., This research was funded by grants number COV20-00080 and COV20-00173 of the 2020 Emergency Call for Research Projects about the SARS-CoV-2 virus and the COVID-19 disease of the Institute of Health ‘Carlos III’, Spanish Ministry of Science and Innovation, and by grant number EQC2019-006240-P of the 2019 Call for Acquisition of Scientific Equipment, FEDER Program, Spanish Ministry of Science and Innovation. This work has been supported by the European Commission through the JRC HUMAINT project. ABR was supported by grant number RTI2018-094465-J funded by the Spanish National Agency of Research. The authors would like to gratefully acknowledge the assistance of the members of the EOD-CBRN Group of the Spanish National Police, whose identities cannot be disclosed, and who are represented here by JMNG. Authors thank continuous support from their institutions.