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Relationship Between Odor Intensity Estimates and COVID-19 Prevalence Prediction in a Swedish Population

Iravani, Behzad; Arshamian, Artin; Ravia, Aharon; Mishor, Eva; Snitz, Kobi; Shushan, Sagit; Roth, Yehudah; Perl, Ofer; Honigstein, Danielle; Weissgross, Reut; Karagach, Shiri; Ernst, Gernot; Okamoto, Masako; Mainen, Zachary; Monteleone, Erminio; Dinnella,

CHEMICAL SENSES
2020
VL / 45 - BP / 449 - EP / 456
abstract
In response to the coronavirus disease 2019 (COVID-19) pandemic, countries have implemented various strategies to reduce and slow the spread of the disease in the general population. For countries that have implemented restrictions on its population in a stepwise manner, monitoring of COVID-19 prevalence is of importance to guide the decision on when to impose new, or when to abolish old, restrictions. We are here determining whether measures of odor intensity in a large sample can serve as one such measure. Online measures of how intense common household odors are perceived and symptoms of COVID-19 were collected from 2440 Swedes. Average odor intensity ratings were then compared to predicted COVID-19 population prevalence over time in the Swedish population and were found to closely track each other (r = -0.83). Moreover, we found that there was a large difference in rated intensity between individuals with and without COVID-19 symptoms and the number of symptoms was related to odor intensity ratings. Finally, we found that individuals progressing from reporting no symptoms to subsequently reporting COVID-19 symptoms demonstrated a large drop in olfactory performance. These data suggest that measures of odor intensity, if obtained in a large and representative sample, can be used as an indicator of COVID-19 disease in the general population. Importantly, this simple measure could easily be implemented in countries without widespread access to COVID-19 testing or implemented as a fast early response before widespread testing can be facilitated.
117th Global

AccesS level

Green published, Hybrid, Green submitted

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