Using influenza surveillance networks to estimate state-specific prevalence of SARS-CoV-2 in the United States

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Abstract

Analysis of influenza-like illness surveillance data estimates that most SARS-CoV-2 infections in the United States went undetected in March 2020.

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  1. Our take

    In this study, available as a preprint and thus not yet peer reviewed, using influenza-like (ILI) surveillance systems, authors estimated that large surges observed in ILI beginning in March 2020 were due to COVID-19, but by the end of March, the case detection rate across the United States was only 12.5%. Analyses of morbidity and mortality doubling times suggest that SARS-CoV-2 has rapidly spread throughout the country since its introduction on January 15, 2020. Although ILINet is a robust surveillance system, authors make several assumptions in their study and model that contribute to uncertainty, and these results should not be used for hospital surge projections or other healthcare demand forecasts.

    Study design

    modeling-simulation

    Study population and setting

    Leveraging existing …

  2. SciScore for 10.1101/2020.04.01.20050542: (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

    No key resources detected.


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


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study has several limitations. First, the observed ILI surge may represent more than just SARS-CoV-2 infected patients. A second epidemic of a non-seasonal pathogen that presents with ILI could confound our estimates of ILI due to SARS-CoV-2. Alternatively, it is also possible that our use of ILI data has underestimated the prevalence of SARS-CoV-2 within the US. While early clinical reports focused on cough and fever as the …