SARS-CoV-2 among migrants and forcibly displaced populations: A rapid systematic review

  1. Maren Hintermeier
  2. Hande Gencer
  3. Katja Kajikhina
  4. Sven Rohleder
  5. Claudia Hövener
  6. Marie Tallarek
  7. Jacob Spallek
  8. Kayvan Bozorgmehr

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Abstract

No abstract available

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  1. Version published to 10.1016/j.jmh.2021.100056
  2. ScreenIT

    SciScore for 10.1101/2020.12.14.20248152: (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

    Software and Algorithms
    SentencesResources
    The search strategy was twofold: Using scientific databases on the one hand and pertinent websites on the other to identify further relevant articles and grey literature.
    Using scientific
    suggested: None
    We conducted a systematic search query in MEDLINE via PubMed and Web of Science Core Collection (WOS) and searched in the major preprint servers medRxiv and bioRxiv to cover yet unpublished research results in this fast and early time of the current pandemic.
    MEDLINE
    suggested: (MEDLINE, RRID:SCR_002185)
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    bioRxiv
    suggested: (bioRxiv, RRID:SCR_003933)
    10-13] The Covidence software was used for the screening of titles, abstract, and full-texts as well as for quality appraisal.
    Covidence
    suggested: (Covidence, RRID:SCR_016484)
    2.3 Data extraction and Outcomes: Data extraction was performed in Excel 2016 by one reviewer (MH) using a piloted form and checked by a second reviewer (KB) for correctness and completeness of the extracted data.
    Excel
    suggested: None
    Numbers of SARS-CoV-2 cases and respective population size, including data on sub-groups, were visualised in a forest plot along with corresponding 95% confidence intervals calculated by the ‘metaprop’ command in STATA SE 15 (with the “nooverall” option to supress pooling of studies across subgroups due to high heterogeneity).[
    STATA
    suggested: (Stata, RRID:SCR_012763)

    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:
    4.1 Strengths and limitations: To our knowledge, and beyond a bibliometric analysis of SARS-CoV-2 research and migration[38], this is the first review to investigate empirical data available on migrant populations at this stage of the COVID-19 pandemic. The conception of this review as a rapid systematic review made it possible to conduct search, screening, quality appraisal, data extraction and synthesis in a timely manner. At the same time, we had to compromise by restricting the study languages to English and German, which poses a possible limitation to identify all empirical data available on this topic so far. The heterogeneity of studies did not allow for running a meta-analysis with pooled estimates to gain further knowledge about the incidence risk in migrant populations. Furthermore, the body of evidence included is limited by a scarcity of high-quality studies and prone to a wide range of bias (hospital bias, diagnostic bias, selection bias, and misclassification bias) or residual confounding. Mortality studies, for example, did not always adjust for age and comorbidity when comparing migrants and non-migrants (see detailed risk of bias assessment: Appendix C). The inclusion of pre-prints, comments, or letters to the editor reporting empirical data was also a challenge for quality appraisal. Nevertheless, this was necessary in order to find as much empirical data as possible, at the early stage of the pandemic when our search was conducted. Given the dynamic number ...

    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.

  3. Version published to 10.1101/2020.12.14.20248152v1 on medRxiv