# The Use of Biological Sensors and Instrumental Analysis to Discriminate COVID-19 Odor Signatures
## 4 Discussion  
This study demonstrates a multi-modal comparative approach to the detection of COVID-19; the researchers utilized both dogs and HS-SPME-GC-MS to discriminate between COVID-19 statuses using human sweat samples. One of the challenges of many prior COVID-19 detection studies was that dogs were trained with relatively small sample sets, which lacked substantial demographic variation and focused on hospitalized COVID-19 patients [20; 42; 43]. Hospital populations are likely to be more severely affected by COVID-19  
Figure 5: COVID T-shirt LDA model and model performance. Figure 6: No pets in bed, COVID-19 T-shirt LDA model and model performance. and be isolated during care. Whereas asymptomatic or mildly affected individuals are more likely to remain in the community and contribute to the spread of the virus. As such, their inclusion in the sample population is integral to identifying COVID-19 positive individuals in the populace. Another constraint posed by small sample sets, but evaded in this work, is the limited ability to determine the dogs' capacity in generalizing to a broader donor population regarding age, race, and severity of illness, among other factors. Both the dogs and the HS-SPME-GC-MS approach were able to discriminate COVID-19 positive from COVID-19 negative in this community-based population. Obtaining samples from a home environment led to an unexpected confounding factor: the presence of animal hair on the T-shirts. It is important to note that in this study 38.5% of individuals reported sharing their beds with a pet. The dogs' performance was not affected by the presence of animal hair; however, the HS-SPME-GC-MS-informed model was. Despite the presence of animal hair interferents, the results of the study were consistent with the finding of [PERSON] et al. (2022), who similarly tested dogs on samples from 335 individuals from two community screening centers [44]. Recent publications by [PERSON] et al. (2022) and by [PERSON] et al. (2022) tested canine discrimination between COVID-19 positive and COVID-19 negative using sweat samples collected from France, UAE, and Australia [43; 44]. These studies recounted high canine sensitivity and specificity, even reporting dogs could identify positive cases before the PCR test. These studies suggest that dogs could prove to be an effective population screening method [14; 17]. Although the dogs were able to correctly identify and alert to COVID-19 positive samples and distinguish these amongst COVID-19 negative samples in this study, there was considerable variability observed in the dogs' detection accuracy. Overall, the dogs gave correct responses (alerting on positive samples and ignoring negative samples) to 62.5% of the presented positive samples and 90% of the presented negative samples. When the canines were regrouped into high-performance (2/5) and low-performance (3/5) canines, a clear delineation in performance was seen. The high-performance group produced correct responses (alert to positive/pass negative) to 85% of positive samples and 94.8% of negative samples. In contrast, the low-performance group had correct responses to only 46.2% of positive samples and 87.2% of negative samples. It is not always clear which dogs will perform well on specific odor detection tasks, and canine performances can vary widely (see [PERSON] et al. (2017) for an example in diabetic alert dogs [45]). Canine performance is known to vary based upon several factors, including canine-oriented factors such as personality traits [46; 47], specific polymorphisms in olfactory receptor genes [48], and handler-oriented factors, including the identity and familiarity of the handler [49] and the handler's belief about the odor's location and positive/negative status [50]. Identification of the specific VOCs may help provide the tools to evaluate the effects of canine-oriented factors. Further research can explore how to identify potentially high-performing detection dogs prior to training, to prevent significant loss of time and capital.