Accuracy verification of low-cost CO 2 concentration measuring devices for general use as a countermeasure against COVID-19

  1. Yo Ishigaki
  2. Koji Enoki
  3. Shinji Yokogawa

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Abstract

Within the context of the COVID-19 pandemic, CO 2 sensors that measure ventilation conditions and thereby reduce the risk of airborne infection, are gaining increasing attention. We investigated and verified the accuracy of 12 relatively low-cost sensor models that retail for less than $45 and are advertised as infection control measures on a major e-commerce site. Our results indicate that 25% of the tested sensors can be used to identify trends in CO 2 concentration, if correctly calibrated. However, 67% of sensors did not respond to the presence of CO 2 , which suggests that a type of pseudo-technique is used to display the CO 2 concentration. We recommend that these sensors are not suitable for infection prevention purposes. We also found that all 67% of the sensors that did not respond to CO2 responded strongly to alcohol. Owing to the widespread use of alcohol in preventing the spread of infectious diseases, sensors that react to alcohol can display inaccurate values, resulting in inappropriate ventilation behavior. Therefore, we strongly recommended that these sensors not be used. Based on our results, we offer practical recommendations to the average consumer, who does not have special measuring equipment, on how to identify inaccurate CO 2 sensors.

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    SciScore for 10.1101/2021.07.30.21261265: (What is this?)

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

    Table 1: Rigor

    EthicsEuthanasia Agents: Alcohol” refers to the twelfth step of the protocol (CONTROLLED AIR), with 5 ml of alcohol added to the chamber at the step 8 (INJECTION) instead of CO2.
    IRB: This study was approved by the Ethics Committee on Experiments on Human Subjects (approval number of 21005), The University of Electro-communications, located at Chofugaoka 1-5-1, Chofu, Tokyo, Japan.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data availability The raw data of the graphs are available on FigShare.
    FigShare
    suggested: (FigShare, RRID:SCR_004328)

    Results from OddPub: Thank you for sharing your data.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.07.30.21261265v2 on medRxiv
  3. Version published to 10.1101/2021.07.30.21261265v1 on medRxiv