SARS-CoV-2 seroprevalence in the urban population of Qatar: An analysis of antibody testing on a sample of 112,941 individuals

  1. Peter V. Coyle
  2. Hiam Chemaitelly
  3. Mohamed Ali Ben Hadj Kacem
  4. Naema Hassan Abdulla Al Molawi
  5. Reham Awni El Kahlout
  6. Imtiaz Gilliani
  7. Nourah Younes
  8. Ghada Ali A.A. Al Anssari
  9. Zaina Al Kanaani
  10. Abdullatif Al Khal
  11. Einas Al Kuwari
  12. Adeel A. Butt
  13. Andrew Jeremijenko
  14. Anvar Hassan Kaleeckal
  15. Ali Nizar Latif
  16. Riyazuddin Mohammad Shaik
  17. Hanan F. Abdul Rahim
  18. Gheyath K. Nasrallah
  19. Hadi M. Yassine
  20. Mohamed Ghaith Al Kuwari
  21. Hamad Eid Al Romaihi
  22. Mohamed H. Al-Thani
  23. Roberto Bertollini
  24. Laith J. Abu-Raddad

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Abstract

No abstract available

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  1. Version published to 10.1016/j.isci.2021.102646
  2. ScreenIT

    SciScore for 10.1101/2021.01.05.21249247: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved by the HMC and Weill Cornell Medicine-Qatar Institutional Review Boards.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Associations with anti-SARS-CoV-2 positivity, as well as with higher antibody titers (defined as optical density higher than the median value) were investigated using chi-square tests and univariable logistic regression.
    anti-SARS-CoV-2
    suggested: None

    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:
    This study has some limitations. The sample included individuals attending HMC for routine or other clinical care, but this population may not necessarily be representative of the wider urban population of Qatar. Some specimens may have been drawn from CMWs, who are not representative of the urban population. However, the large sample size, equivalent to ∼10% of the urban population of Qatar, as well as the probabilistic weighting used in the analysis may have reduced inherent biases in our sample. Laboratory methods were based on high-quality, validated commercial platforms, such as the Roche platform used for serological testing [16,31]. The Roche platform is one of the most extensively used and investigated commercial platforms, with a specificity ≥99.8% [16,32,33] and a sensitivity ≥89% [12,31,33]. However, it is possible that the less-than-perfect sensitivity, especially for those with recent infections, may have underestimated the actual seroprevalence. Indeed, a recent investigation of the performance of three automated, commercial, serological platforms in Qatar, including the Roche platform, found that each of them missed ≥20% of individuals with past or current infections [34]. In conclusion, fewer than two in every 10 individuals in the urban population of Qatar had detectable antibodies against SARS-CoV-2, suggesting that this population is still well below the herd immunity threshold and is potentially at risk from a subsequent epidemic wave. This emphasizes the ...

    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 10.1101/2021.01.05.21249247 on medRxiv