# The Use of Biological Sensors and Instrumental Analysis to Discriminate COVID-19 Odor Signatures
Since SARS-CoV-2 is capable of rapid transmission, and has proven to result in drastic health consequences, there is a pressing need for effective surveillance testing. Currently, the most sensitive testing methods for SARS-CoV-2 are fairly time consuming, and the rapid tests can fail to detect low viral loads. Nucleic amplification detection methods such as reverse-transcriptase polymerase chain reaction (RT-PCR) are the gold standard for the diagnosis of SARS-CoV-2. Although RT-PCR testing has a relatively high sensitivity, false negatives can occur for several reasons, including viral content below the test's limit of detection, poor sample collection, and faulty technique in sample testing [10]. False negative results can lead to increased spreading of the virus from unknowingly infected individuals [11]. Additionally, those with asymptomatic COVID-19 expression may not proactively seek out testing due to their lack of symptoms [12]. Due to disease state misdiagnosis and lack of detection in asymptomatic carriers, there is a persisting need for the deployment of noninvasive population screening for COVID-19. This study investigates two prospective screening methodologies applied to clothing worn by individuals in the community who had been tested for COVID-19: the first is the use of trained detection dogs, and the second is the analysis of samples via headspace-solid phase-microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). These noninvasive biological and instrumental systems were applied in parallel to discriminate the complex odor signature from COVID-19 body odor samples. Current research demonstrates that dogs can be trained to detect hypoglycemia [13], lung cancer [14], ovarian cancer [15; 16], prostate cancer [17], and urinary tract infections [18]. More recently, several research groups have trained dogs to identify signature volatile organic compounds (VOCs) of SARS-CoV-2 in a variety of mediums; including pharyngeal secretions [19], urine [20], saliva [20], sweat [21; 22], and breath [23; 24]. However, the distinct VOCs associated with the SARS-CoV-2 virus have been minimally explored outside of VOCs in exhaled breath [25; 26]. VOCs are produced by cells during metabolic processes, inflammatory processes, and oxidative stress. These compounds are released from the human body via breath, urine, feces, and blood [27]. While several studies have identified key COVID-19-associated VOCs in breath [23; 24; 25; 26; 28; 29; 30], it can be risky to utilize breath as a medium for detection in dogs, since breath from positive patients contains live virus [28; 31] and dogs are susceptible to contracting COVID-19. In contrast, sweat from COVID-19 positive patients is a safer sample source, containing no live virus [32]. VOCs associated with the SARS-CoV-2 virus in sweat samples can be identified using headspace analysis via solid phase microextraction (SPME), which allows for the capture of gaseous analytes onto a coated sorbent surface, the SPME fiber [33]. Once on the SPME fiber, the analytes can be transferred to another instrument for desorption and analysis. HS-SPME is often used in conjunction with gas chromatography-mass spectrometry (GC-MS), where the GC-MS separates and analyzes the compounds captured by the HS-SPME procedure. Various works have been published on the use of HS-SPME-GC-MS for the detection and characterization of VOCs from human specimens, including sweat, blood, saliva, urine, breath, hair, and fingemails (see [34] for a review). Complementary detection of VOCs by biosensors (dogs) and analytical instrumentation (HS-SPME-GC-MS) can narrow down areas of volatile biomarkers [16] and allow for further characterization of these unique VOC profiles, providing a critical step forward for the detection of COVID-19. In this study, we compared the performance of dogs and the headspace analysis of COVID-19 samples by HS-SPME-GC-MS.