Tracking COVID-19 using taste and smell loss Google searches is not a reliable strategy

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Abstract

Web search tools are widely used by the general public to obtain health-related information, and analysis of search data is often suggested for public health monitoring. We analyzed popularity of searches related to smell loss and taste loss, recently listed as symptoms of COVID-19. Searches on sight loss and hearing loss, which are not considered as COVID-19 symptoms, were used as control. Google Trends results per region in Italy or state in the US were compared to COVID-19 incidence in the corresponding geographical areas. The COVID-19 incidence did not correlate with searches for non-symptoms, but in some weeks had high correlation with taste and smell loss searches, which also correlated with each other. Correlation of the sensory symptoms with new COVID-19 cases for each country as a whole was high at some time points, but decreased (Italy) or dramatically fluctuated over time (US). Smell loss searches correlated with the incidence of media reports in the US. Our results show that popularity of symptom searches is not reliable for pandemic monitoring. Awareness of this limitation is important during the COVID-19 pandemic, which continues to spread and to exhibit new clinical manifestations, and for potential future health threats.

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  1. SciScore for 10.1101/2020.05.07.20093955: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The collected data were used to build the graphs in Figures 1 and 2 using the RStudio software36.
    RStudio
    suggested: (RStudio, RRID:SCR_000432)

    Results from OddPub: Thank you for sharing your code and data.


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The same limitations will likely apply to new COVID-19 symptoms that are being discovered, such as skin lesions19, impairment of chemesthesis (a chemosensory modality that allows the perception of burning, cooling or tingling triggered by molecules)18, and more16. As the pandemic continues to spread around the world, and secondary waves are expected, monitoring of COVID-19 remains of great importance20-22 and strategies for geographic monitoring of COVID-19 hotspots are being developed23. Furthermore, future pandemics may, unfortunately, emerge24. The phenomen described here suggests that a correlation between interest in novel symptoms of infectious disease and the number of new cases has an initial spike (the “surprise rise”) and subsequently drops off to a new baseline due to “knowledge saturation”. This lesson may be of general practical value for public health. The “surprise rise” effect has been successfully employed by several groups for outbreaks forecasting using specific Google searches. The increase in volume of searches has been shown to predict the outbreaks from several days to weeks earlier25-27. On the other hand, the “knowledge saturation” make the monitoring of the disease through the same tools more challenging over time. The shortcomings of methods that rely on self-reporting should be kept in mind also in analyzing results from the various self-reporting apps28-30, and underscore the crucial role of independent epidemiological tools, such as sewage monito...

    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.

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