Direct Observation of Repeated Infections With Endemic Coronaviruses

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Abstract

Background

Although the mechanisms of adaptive immunity to pandemic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are still unknown, the immune response to the widespread endemic coronaviruses HKU1, 229E, NL63, and OC43 provide a useful reference for understanding repeat infection risk.

Methods

Here we used data from proactive sampling carried out in New York City from fall 2016 to spring 2018. We combined weekly nasal swab collection with self-reports of respiratory symptoms from 191 participants to investigate the profile of recurring infections with endemic coronaviruses.

Results

During the study, 12 individuals tested positive multiple times for the same coronavirus. We found no significant difference between the probability of testing positive at least once and the probability of a recurrence for the betacoronaviruses HKU1 and OC43 at 34 weeks after enrollment/first infection. We also found no significant association between repeat infections and symptom severity, but found strong association between symptom severity and belonging to the same family.

Conclusions

This study provides evidence that reinfections with the same endemic coronavirus are not atypical in a time window shorter than 1 year and that the genetic basis of innate immune response may be a greater determinant of infection severity than immune memory acquired after a previous infection.

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  1. SciScore for 10.1101/2020.04.27.20082032: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Participants (or their guardians, if minors) provided informed consent after reading a detailed description of the study (CUMC IRB AAAQ4358).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    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: We detected the following sentences addressing limitations in the study:
    However, the seasonality of endemic coronaviruses, which are mostly absent during the summer months, and the relative magnitude across years of seasonal coronavirus epidemics are limitations. In US the prevalence of OC43 during the 2016–17 season was much higher than during the 2017–18 season, whereas the opposite trend was observed for HKU1 [22]. Moreover, our estimates of infection and re-infection probabilities must be considered as a lower bound, due to the occurrence of weekly swabs missed by the participants and due to the design of the study itself, which may have missed infections of short duration in between consecutive weekly tests. Nevertheless, this study confirms that re-infections with the same coronavirus type occur in a time window shorter than 1 year, and finds no significant association between repeat infections and symptom severity. Instead, it provides evidence of possible genetic determinants of innate immune response, as individuals asymptomatic during first infection did not experience symptoms during subsequent infections, and members of the same families reported similar symptom severity. We recognize that the self-reporting of symptoms is an important limitation in this analysis and that parents reported symptoms for their dependents, which possibly introduced bias. Moreover, the majority of the repeated coronavirus infections were found in children, a cohort more vulnerable to infection because of their immature immune system [23], and 26% of the ep...

    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

    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.