A Novel Approach to Monitoring the COVID-19 Pandemic using Emergency Department Discharge Diagnoses

  1. Herbert C. Duber
  2. M. Kennedy Hall
  3. Karl Jablonowski
  4. Susan A. Stern
  5. Ali H Mokdad
  6. Abraham D Flaxman

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Abstract

Introduction

Tracking the COVID-19 pandemic using existing metrics such as confirmed cases and deaths are insufficient for understanding the trajectory of the pandemic and identifying the next wave of cases. In this study, we demonstrate the utility of monitoring the daily number of patients with COVID-like illness (CLI) who present to the Emergency Department (ED) as a tool that can guide local response efforts.

Methods

Using data from two hospitals in King County, WA, we examined the daily volume of CLI visits, and compare them to confirmed COVID cases and COVID deaths in the County. A linear regression model with varying lags is used to predict the number of daily COVID deaths from the number of CLI visits.

Results

CLI visits appear to rise and peak well in advance of both confirmed COVID cases and deaths in King County. Our regression analysis to predict daily deaths with a lagged count of CLI visits in the ED showed that the R 2 value was maximized at 14 days.

Conclusions

ED CLI visits are a leading indicator of the pandemic. Adopting and scaling up a CLI monitoring approach at the local level will provide needed actionable evidence to policy makers and health officials struggling to confront this health challenge.

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  1. ScreenIT

    SciScore for 10.1101/2020.06.09.20126508: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

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

    About SciScore

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  2. Version published to 10.1101/2020.06.09.20126508v1 on medRxiv