COVID-Anosmia Checker: A rapid and low-cost alternative tool for mass screening of COVID-19

  1. Budhaditya Basu
  2. Paul Ann Riya
  3. Joby Issac
  4. Surendran Parvathy
  5. Biju Surendran Nair
  6. Pradipta Tokdar
  7. Devika Sanal Kumar
  8. Pranav Ravi Kulkarni
  9. Gowtham Hanumanram
  10. Mohanan Jagadeesan
  11. Prasanna Karthik Suthakaran
  12. Lal Devayani Vasudevan Nair
  13. Rosy Vennila
  14. Rajendran Kannan
  15. Balarama Kaimal
  16. Gopa Kumar Anoop
  17. Iype Joseph
  18. Radhakrishnan Nair
  19. Saji George
  20. Jackson James
  21. Madhavan Radhakrishna Pillai

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Abstract

Background

COVID-19 curve can be flattened by adopting mass screening protocols with aggressive testing and isolating infected populations. The current approach largely depends on RT-PCR/rapid antigen tests that require expert personnel resulting in higher costs and reduced testing frequency. Loss of smell is reported as a major symptom of COVID-19, however, a precise olfactory testing tool to identify COVID-19 patient is still lacking.

Methods

To quantitatively check for the loss of smell, we developed an odor strip, “ COVID-Anosmia checker” , spotted with gradients of coffee and lemon grass oil. We validated its efficiency in healthy and COVID-19 positive subjects. A trial screening to identify SARS-CoV-2 infected persons was also carried out to check the sensitivity and specificity of our screening tool.

Findings

It was observed that COVID positive participants were hyposmic instead of being anosmic when they were subjected to smelling higher odor concentration. Our tool identified 97% of symptomatic and 94% of asymptomatic COVID-19 positive subjects after excluding most confounding factors like concurrent chronic sinusitis. Further, it was possible to reliably predict COVID-19 infection by calculating a loss of smell score with 100% specificity. We coupled this tool with a mobile application, which takes the input response from the user, and can readily categorize the user in the appropriate risk groups.

Conclusion

Loss of smell can be used as a reliable marker for screening for COVID-19. Our tool can be used for first-line screening to trace out COVID-19 infection effectively. It can be used in difficult to reach geographical locations.

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  1. ScreenIT

    SciScore for 10.1101/2020.10.28.20221200: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Inclusion criteria were: Age 20-60 years, with an oral consent to participate.
    IRB: The study was approved by the Institutional Human Ethics Committee of Rajiv Gandhi Center for Biotechnology (RGCB/IHEC/250/2020/28) and Saveetha Medical College Hospital (002/08/2020/IEC/SMCH).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableBoth males and females were included in the study.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical Analysis: Data were analyzed using IBM SPSS 20.0, Microsoft Excel, and visualized using R Studio ggplot2 package.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    R Studio
    suggested: None
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.10.28.20221200v1 on medRxiv
  3. Version published to 10.1101/2020.10.28.20221200v2 on medRxiv