Preferential observation of large infectious disease outbreaks leads to consistent overestimation of intervention efficacy

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Abstract

Data from infectious disease outbreaks in congregate settings are often used to elicit clues about which types of interventions may be useful in other facilities. This is commonly done using before-and-after comparisons in which the infectiousness of pre-intervention cases is compared to that of post-intervention cases and the difference is attributed to intervention impact. In this manuscript, we show how a tendency to preferentially observe large outbreaks can lead to consistent overconfidence in how effective these interventions actually are. We show, in particular, that these inferences are highly susceptible to bias when the pathogen under consideration exhibits moderate-to-high amounts of heterogeneity in infectiousness. This includes important pathogens such as SARS-CoV-2, influenza, Noroviruses, HIV, Tuberculosis, and many others

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  1. SciScore for 10.1101/2020.11.02.20224832: (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: 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.

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