Recent anecdotal and scientific reports have provided evidence of a link between COVID-19 and chemosensory impairments such as anosmia. However, these reports have downplayed or failed to distinguish potential effects on taste, ignored chemesthesis, and generally lacked quantitative measurements. Here, we report the development, implementation and initial results of a multi-lingual, international questionnaire to assess self-reported quantity and quality of perception in three distinct chemosensory modalities (smell, taste, and chemesthesis) before and during COVID-19. In the first 11 days after questionnaire launch, 4039 participants (2913 women, 1118 men, 8 other, ages 19-79) reported a COVID-19 diagnosis either via laboratory tests or clinical assessment. Importantly, smell, taste and chemesthetic function were each significantly reduced compared to their status before the disease. Difference scores (maximum possible change ±100) revealed a mean reduction of smell (-79.7 ± 28.7, mean ± SD), taste (-69.0 ± 32.6), and chemesthetic (-37.3 ± 36.2) function during COVID-19. Qualitative changes in olfactory ability (parosmia and phantosmia) were relatively rare and correlated with smell loss. Importantly, perceived nasal obstruction did not account for smell loss. Furthermore, chemosensory impairments were similar between participants in the laboratory test and clinical assessment groups. These results show that COVID-19-associated chemosensory impairment is not limited to smell, but also affects taste and chemesthesis. The multimodal impact of COVID-19 and lack of perceived nasal obstruction suggest that SARS-CoV-2 infection may disrupt sensory-neural mechanisms.

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In a preregistered, cross-sectional study we investigated whether olfactory loss is a reliable predictor of COVID-19 using a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n=4148) or negative (C19-; n=546) COVID-19 laboratory test outcome. Logistic regression models identified univariate and multivariate predictors of COVID-19 status and post-COVID-19 olfactory recovery. Both C19+ and C19- groups exhibited smell loss, but it was significantly larger in C19+ participants (mean±SD, C19+: -82.5±27.2 points; C19-: -59.8±37.7). Smell loss during illness was the best predictor of COVID-19 in both univariate and multivariate models (ROC AUC=0.72). Additional variables provide negligible model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms (e.g., fever). Olfactory recovery within 40 days of respiratory symptom onset was reported for ~50% of participants and was best predicted by time since respiratory symptom onset. We find that quantified smell loss is the best predictor of COVID-19 amongst those with symptoms of respiratory illness. To aid clinicians and contact tracers in identifying individuals with a high likelihood of having COVID-19, we propose a novel 0-10 scale to screen for recent olfactory loss, the ODoR-19. We find that numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (4<OR<10). Once independently validated, this tool could be deployed when viral lab tests are impractical or unavailable.

The objective of this study was to develop a semantically labeled hedonic scale (LHS) that would yield ratio-level data on the magnitude of liking/disliking of sensation equivalent to that produced by magnitude estimation (ME). The LHS was constructed by having 49 subjects who were trained in ME rate the semantic magnitudes of 10 common hedonic descriptors within a broad context of imagined hedonic experiences that included tastes and flavors. The resulting bipolar scale is statistically symmetrical around neutral and has a unique semantic structure. The LHS was evaluated quantitatively by comparing it with ME and the 9-point hedonic scale. The LHS yielded nearly identical ratings to those obtained using ME, which implies that its semantic labels are valid and that it produces ratio-level data equivalent to ME. Analyses of variance conducted on the hedonic ratings from the LHS and the 9-point scale gave similar results, but the LHS showed much greater resistance to ceiling effects and yielded normally distributed data, whereas the 9-point scale did not. These results indicate that the LHS has significant semantic, quantitative, and statistical advantages over the 9-point hedonic scale.

If a chi‐squared analysis were to be performed to determine whether preferences were significant in a paired preference test, the appropriate expected frequencies in the analysis would represent those that would occur should the consumers have no preference. One way of determining these ‘no preference’frequencies, for a particular test situation, would be to note the preference responses obtained when the stimuli were putatively identical. Over 2000 consumers were given paired preference tests in which the stimuli were putatively identical. Response conditions and consumer groups were varied and the proportions of preference and no preference responses were noted. In a preliminary experiment, further research was seen to be justified when for putatively identical stimuli, judges did not exclusively express lack of preference; many expressed a preference for one or other of the stimuli. Further experiments were conducted using a written response condition and putatively identical potato chips (potato crisps) as stimuli. Using a single ‘no preference’option, variation in the placement of this option at either first, second or third place on the response sheet had no significant effect on the response frequencies. The proportion of ‘no preference’responses was approximately 30% in all cases. A previously reported 40‐20‐40 distribution was not always confirmed. The experiment was repeated with Korean consumers; these had fewer ‘no preference’responses. Deriving preferences from hedonic scales, rather than having judges respond to preference options, increased the proportion of ‘no preference’responses, with American judges still having more than Korean judges. Yet there are logical objections to extracting preference data from hedonic scales. Increasing the number of ‘no preference’options to two or three, had the effect of increasing the number of ‘no preference’responses up to as much as approximately 60%. Extending the results to Koreans, using two ‘no preference’options, it was seen that only the judges in an anonymous response condition had significantly fewer ‘no preference’responses than Americans. The use of these response frequencies as expected frequencies in chi squared analyses was illustrated, after adjustments for counterbalancing.