Potential Protective Effect from COVID-19 Conferred by Altitude: A Longitudinal Analysis in Peru During Full Lockdown

  1. Timothy M. Thomson
  2. Fresia Casas
  3. Harold Andre Guerrero
  4. Rómulo Figueroa-Mujíca
  5. Francisco C. Villafuerte
  6. Claudia Machicado

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Abstract

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  1. Version published to 10.1089/ham.2020.0202
  2. ScreenIT

    SciScore for 10.1101/2020.08.03.20167262: (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
    Values for all variables were row median-normalized and subjected to PCA and CT as implemented in XLSTAT.
    XLSTAT
    suggested: (XLSTAT, RRID:SCR_016299)
    Generation of heatmaps: For heatmap generation, variables were row-normalized and heatmaps generated with the aid of Morpheus (https://software.broadinstitute.org/morpheus/).
    https://software.broadinstitute.org/morpheus/
    suggested: (Morpheus by Broad Institute, RRID:SCR_017386)
    Other statistical analyses: For non-paired, non-parametric data comparisons, Mann-Whitney tests were performed on GraphPad.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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, these tests are applied to the general public free of charge by the Peruvian national health system, and there is no evidence of shortage of serological tests, although they are unevenly distributed throughout the territory (see Study Limitations). Likewise, high poverty levels could limit the availability of health care and may be expected to be associated with elevated case and death rates as observed elsewhere (e.g., https://www1.nyc.gov/site/doh/covid/covid-19-data.page). Contrary to this expectation, in our multivariate analyses, high poverty indexes were associated with higher altitude and lower, not higher, death rates. In conclusion, altitude appears to confer protection from COVID-19 incidence and death independent of population density and not offset by high poverty levels. The latter observation is at odds with the findings of the OpenSAFELY study, which detected an increased risk of COVID-19 death with greater deprivation in the United Kingdom8, not fully explained by pre-existing conditions or other risk factors. This reinforces the notion that additional local conditions are significant modifiers of sensitivity to COVID-19. We have found that the apparent protective effect of altitude was very strong when comparing populations below and above the accepted high-altitude threshold (2,500 m), with relative risks for low-altitude populations, both in coastal and Amazonian regions, between 6.5 and over 11-fold for cases and over 6.5 and 21.6-fold for deaths,...

    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 10.1101/2020.08.03.20167262v4 on medRxiv
  4. Version published to 10.1101/2020.08.03.20167262v3 on medRxiv
  5. Version published to 10.1101/2020.08.03.20167262v1 on medRxiv
  6. Version published to 10.1101/2020.08.03.20167262v2 on medRxiv