Factors associated with the spatial heterogeneity of the first wave of COVID-19 in France: a nationwide geo-epidemiological study

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

No abstract available

Article activity feed

  1. SciScore for 10.1101/2020.09.17.20196360: (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 variableAs male sex and older age are associated with increased severity (32–35), we extracted the population age and sex structure estimated in 2020 for each department, from the French national statistics institute (Institut national de la statistique et des études économiques INSEE) (36).

    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:
    Our study may also have suffered from several additional limitations. We only analysed COVID-19 in-hospital data. Testing was indeed too limited in France during the first epidemic wave to provide an accurate estimation of outpatient incidence. Besides, casualties in retirement homes have not yet been made available at department level. Hospitalization criteria may not be homogeneous across departments, and milder cases may have been hospitalized more frequently in less affected departments or depending on local care policy (63). Age of hospitalized patients have not been made available at department level to account for these differences. This may partly explain why our multivariate analysis explained only 53.1% of lethality, with a slight overestimation of the lethality rate in Bouches-du-Rhône. Additional factors may have been associated with lethality, needing further analysis at a more accurate scale. Finally, we performed an ecological study, not an individual population study, which introduces classical ecological fallacy, and therefore means we cannot infer any direct individual risk (64). In conclusion, our study could explain a great part of the spatial heterogeneity of in-hospital COVID-19 incidence and mortality across metropolitan France, and to a lesser extent of its lethality. We highlighted that the population age structure was an important determinant of the mortality and lethality at the department level, and that the lockdown policy was an effective way to ...

    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.