Recent Smell Loss Is the Best Predictor of COVID-19 Among Individuals With Recent Respiratory Symptoms

Abstract

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.

Keywords: anosmia; chemosensory; coronavirus; hyposmia; olfactory; prediction.

Figure 1.

Flow diagram showing participant demographics. Participants included in the prediction of COVID-19 status are framed in blue. Participants included in the smell recovery models are framed in green. Participants included in the replication of a previous study (Parma, Ohla, et al. 2020; Parma, Veldhuizen, et al. 2020) are framed in orange. Gender percentages omit <1% of participants who answered “other” or “preferred not to say.” Participants described in the green boxes are a subset of those described in the blue boxes. n = number of participants; yo = age in years; W = women; M = men; unclear COVID diagnosis = responses “No—I do not have any symptoms,” “Don’t know” or “Other” to survey Question 8 (“Have you been diagnosed with COVID-19?”).

Figure 2.

Chemosensory ability and nasal obstruction in C19+ and C19− participants. Self-reported smell (A, B), taste (C, D), chemesthesis (E, F), and nasal obstruction (G, H: formulated as “How blocked was your nose?”) before and during respiratory illness in C19+ (darker shades) and C19− (lighter shades) participants. Ratings were given on 0–100 visual analog scales. Left panels (A, C, E, G) show mean values. Right panels (B, D, F, H) show distributions of the change scores (during minus before). Thicker sections indicate relatively more subjects (higher density of responses). The thick black horizontal bar indicates the median, the shaded area within each violin indicates the interquartile range. Each dot represents the rating of a single participant. * indicates P < 10^–4, ** indicates P < 10^–23.

Figure 3.

Smell loss is the strongest predictor of COVID-19 status. (A) A normalized measure of association (Cramer’s V) between binary or categorical responses on COVID-19 status. V = 0 reflects no association between the response and COVID-19 status; V = 1 reflects a perfect association; V > 0.1 is considered a meaningful association. Variables in red are positively associated with C19+ (odds ratio > 1); variables in blue are negatively associated with C19+ (odds ratio < 1). (B) Logistic regression is used to predict COVID-19 status from individual variables. Top-10 single variables are ranked by performance (cross-validated area under the ROC curve, AUC). Chemosensory-related variables (bold) show greater predictive accuracy than non-chemosensory variables (non-bold). Responses provided on the numeric scale (italic) were more informative than binary responses (non-italic). Red arrows indicate differences in prediction quality (in AUC) between variables. (C) Adding variables to “Smell During Illness” results in little improvement to the model; only Days Since Onset of Respiratory Symptoms (DOS) relative to survey completion date yields meaningful improvement. (D) ROC curves for several models. A model using “Smell during illness” (Smell Only, abbreviated “Smell” in the figure) is compared against models containing this feature along with DOS, as well as models including the three cardinal CDC variables (fever, dry cough, difficulty breathing). “Full” indicates a regularized model fit using 70 survey variables, which achieves prediction accuracy similar to the parsimonious model “Smell Only + DOS.”

Figure 4.

Smell loss, recovery, and time course. (A, B) Joint distribution of smell loss (during minus before illness ratings) and smell recovery (after minus during illness ratings) for C19+ (A) and C19− (B) participants. Darker color indicates a higher probability density; the color map is shared between (A) and (B); dashed lines are placed at a third of the way across the rating scale to aid visualization of the clusters. Severe smell loss that is either persistent (lower left) or recovered (upper left) was more common in C19+ than C19−. n indicates the number of participants in each panel. % indicates the percentage of participants of the given COVID status in each quadrant. (C) In C19+ participants who lost their sense of smell (Recovered Smell + Persistent Smell Loss), the degree of smell recovery (right y axis) increased over ~30 days since onset of respiratory symptoms before plateauing; the degree of reported smell change (left y axis) did not vary in that window of observation. Solid lines indicate the mean of the measure, the shaded region indicates the 95% confidence interval.

Figure 5.

The odds of a COVID-19 diagnosis as a function of olfactory ability in individuals with respiratory symptoms. (A) The solid line indicates the probability of a COVID-19 diagnosis as a function of “Smell during illness” ratings in our sample. The shaded region indicates the 95% confidence interval. (B) The solid line expresses the probability of a COVID-19+ diagnosis as a function of “Smell during illness” in odds (p/[1−p]); it is shown on a logarithmic scale. The shaded region indicates the 95% confidence interval. (C) Stylized depiction of change in the odds of a COVID-19 diagnosis and of the odds ratio. (D) The ODoR-19 tool. After healthcare providers or contact tracers have excluded previous smell and/or taste disorders (such as those resulting from head trauma, chronic rhinosinusitis, or previous viral illness) in patients with respiratory symptoms, the patient can be asked to rate their current ability to smell on a scale from 0 to 10, with 0 being no sense of smell and 10 being excellent sense of smell. If the patient reports a value below or equal to 3, there is a high (red) or moderate (orange) probability that the patient has COVID-19. Values in yellow (ratings above 3) cannot rule out COVID-19.