Investigating the Use of SARS-CoV-2 (COVID-19) Odor Expression as a Non-Invasive Diagnostic Tool-Pilot Study.

Since the beginning of the COVID-19 pandemic, there has been enormous interest in the development of measures that would allow for the swift detection of the disease. The rapid screening and preliminary diagnosis of SARS-CoV-2 infection allow for the instant identification of possibly infected individuals and the subsequent mitigation of the disease spread. Herein, the detection of SARS-CoV-2-infected individuals was explored using noninvasive sampling and low-preparatory-work analytical instrumentation. Hand odor samples were obtained from SARS-CoV-2-positive and -negative individuals. The volatile organic compounds (VOCs) were extracted from the collected hand odor samples using solid phase microextraction (SPME) and analyzed using gas chromatography coupled with mass spectrometry (GC-MS). Sparse partial least squares discriminant analysis (sPLS-DA) was used to develop predictive models using the suspected variant sample subsets. The developed sPLS-DA models performed moderately (75.8% (±0.4) accuracy, 81.8% sensitivity, 69.7% specificity) at distinguishing between SARS-CoV-2-positive and negative -individuals based on the VOC signatures alone. Potential markers for distinguishing between infection statuses were preliminarily acquired using this multivariate data analysis. This work highlights the potential of using odor signatures as a diagnostic tool and sets the groundwork for the optimization of other rapid screening sensors such as e-noses or detection canines.

The Use of Biological Sensors and Instrumental Analysis to Discriminate COVID-19 Odor Signatures.

The spread of SARS-CoV-2, which causes the disease COVID-19, is difficult to control as some positive individuals, capable of transmitting the disease, can be asymptomatic. Thus, it remains critical to generate noninvasive, inexpensive COVID-19 screening systems. Two such methods include detection canines and analytical instrumentation, both of which detect volatile organic compounds associated with SARS-CoV-2. In this study, the performance of trained detection dogs is compared to a noninvasive headspace-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) approach to identifying COVID-19 positive individuals. Five dogs were trained to detect the odor signature associated with COVID-19. They varied in performance, with the two highest-performing dogs averaging 88% sensitivity and 95% specificity over five double-blind tests. The three lowest-performing dogs averaged 46% sensitivity and 87% specificity. The optimized linear discriminant analysis (LDA) model, developed using HS-SPME-GC-MS, displayed a 100% true positive rate and a 100% true negative rate using leave-one-out cross-validation. However, the non-optimized LDA model displayed difficulty in categorizing animal hair-contaminated samples, while animal hair did not impact the dogs' performance. In conclusion, the HS-SPME-GC-MS approach for noninvasive COVID-19 detection more accurately discriminated between COVID-19 positive and COVID-19 negative samples; however, dogs performed better than the computational model when non-ideal samples were presented.

Preliminary accuracy of COVID-19 odor detection by canines and HS-SPME-GC-MS using exhaled breath samples.

The novel coronavirus SARS-CoV-2, since its initial outbreak in Wuhan, China has led to a worldwide pandemic and has shut down nations. As with any outbreak, there is a general strategy of detection, containment, treatment and/or cure. The authors would argue that rapid and efficient detection is critical and required to successful management of a disease. The current study explores and successfully demonstrates the use of canines to detect COVID-19 disease in exhaled breath. The intended use was to detect the odor of COVID-19 on contaminated surfaces inferring recent deposition of infectious material from a COVID-19 positive individual. Using masks obtained from hospitalized patients that tested positive for COVID-19 disease, four canines were trained and evaluated for their ability to detect the disease. All four canines obtained an accuracy >90% and positive predictive values ranging from ~73 to 93% after just one month of training.

Fabric-Phase Sorptive Membrane Array As a Noninvasive In Vivo Sampling Device For Human Exposure To Different Compounds.

This study introduces an innovative device for the noninvasive sampling and chromatographic analysis of different compounds present in exhaled breath aerosol (EBA). The new sampling device, especially in light of the recent COVID-19 pandemic that forced many countries to impose mandatory facemasks, allows an easy monitoring of the subject's exposure to different compounds they may come in contact with, actively or passively. The project combines the advantages of a fabric-phase sorptive membrane (FPSM) as an in vivo sampling device with a validated LC-MS/MS screening procedure able to monitor more than 739 chemicals with an overall analysis time of 18 min. The project involves the noninvasive in vivo sampling of the EBA using an FPSM array inserted inside an FFP2 mask. The study involved 15 healthy volunteers, and no restrictions were imposed during or prior to the sampling process regarding the consumption of drinks, food, or drugs. The FPSM array-LC-MS/MS approach allowed us to effectively exploit the advantages of the two complementary procedures (the convenient sampling by an FPSM array and the rapid analysis by LC-MS/MS), obtaining a powerful and green tool to carry out rapid screening analyses for human exposure to different compounds. The flexible fabric substrate, the sponge-like porous architecture of the high-efficiency sol-gel sorbent coating, the availability of a large cache of sorbent coatings, including polar, nonpolar, mixed mode, and zwitterionic phases, the easy installation into the facemask, and the possibility of sampling without interrupting regular activities provide FPSMs unparalleled advantages over other sampling techniques, and their applications are expected to expand to many other clinical or toxicological studies.