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

  1. Behzad Iravani
  2. Artin Arshamian
  3. Aharon Ravia
  4. Eva Mishor
  5. Kobi Snitz
  6. Sagit Shushan
  7. Yehudah Roth
  8. Ofer Perl
  9. Danielle Honigstein
  10. Reut Weissgross
  11. Shiri Karagach
  12. Gernot Ernst
  13. Masako Okamoto
  14. Zachary Mainen
  15. Erminio Monteleone
  16. Caterina Dinnella
  17. Sara Spinelli
  18. Franklin Mariño-Sánchez
  19. Camille Ferdenzi
  20. Monique Smeets
  21. Kazushige Touhara
  22. Moustafa Bensafi
  23. Thomas Hummel
  24. Noam Sobel
  25. Johan N Lundström

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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.

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    SciScore for 10.1101/2020.05.07.20094516: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: Data collection and analyses were approved by both the Israeli Edith Wolfson Medical Centre Helsinki Committee and the Swedish Institutional Review Board (Etikprövningsnämnden, 2020-01577).
    Consent: Participants did not receive any form of monetary compensation for their participation and consent was waived.
    RandomizationFrom March to April, Folkhälsomyndigheten randomly sampled 738 individuals in the Stockholm region and based on this data, together with available data from the healthcare system and the contagion factor of the SARS-CoV-2 virus, modelled the prevalence of COVID-19 in the Stockholm population over time.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All statistical analyses were carried out within the MATLAB (version 2019b) environment with Statistical and Machine Learning toolbox.
    MATLAB
    suggested: (MATLAB, RRID:SCR_001622)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1093/chemse/bjaa034
  3. Version published to 10.1101/2020.05.07.20094516v1 on medRxiv